Discover how SQE is advancing Industry 4.0 with quantum-secure blockchain to build operational trust across manufacturing systems. Learn how to secure device identity, machine communications, and data flows—without disruptive infrastructure changes.
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Operational Trust in Industry 4.0: Quantum-Secure Blockchain for Manufacturing and Automation
72 views Mar 19, 2026
Discover how SQE is advancing Industry 4.0 with quantum-secure blockchain to build operational trust across manufacturing systems. Learn how to secure device identity, machine communications, and data flows—without disruptive infrastructure changes.
Transcript
0:00
pyramid and you know I have the benefit as uh I guess the doctor on demand the
0:05
doctor on demand at the Bergkshire innovation center of having seen you through uh the stage 2 accelerator
0:12
program and through networking events and supporting you I’ve been able to see your company grow thrive um and I’ve
0:20
also you know not everybody knows what SQE really is though right so and also
0:25
I’m always interested I feel like I work for Entrepreneur magazine why did you smart SQE in the first place. So tell us
0:32
about SQE, you know, briefly. I know, you know, time is of the absence and we need to get on to the demo
0:38
and and why did you start it? Um, so back in 2000, I was working on a
0:44
long uh working on a project for a long time and and if you could get close to the mic because you say brilliant things and
0:50
we can’t miss those things. So I was working on this project and uh it took me a long time to uh to
0:57
implement the project. I finally finished it and I realized that that I needed to add security to the project.
1:04
It turns out that the cost of security was higher than the cost of my uh project my my products and so at that
1:11
point I said oh what can I do? I wanted to implement the standard technologies but I found that they were just the
1:17
chipset that I had to use were just too expensive and implementation was even more expensive and more importantly
1:23
securing the keys for for the this IoT device was even more expensive. It just
1:30
turns out that it was not feasible and that is a problem that exists to today. So uh I uh having a background in
1:38
mathematics a bit of quantum physics uh but definitely engineering it just hit
1:43
me that I can actually simulate quantum entanglement. So it was through a pragmatic absolutely
1:48
you know real world need that you became this utilitarian inventor visionary. Yeah the need is the mother invention by
1:55
definition. So now now if you could segue uh industry 4.0 I know is interesting and so is blockchain, but very rarely do
2:02
people talk about the interrelatedness of the two. Could you do that for a moment for us? Sure. Um, they they absolutely they’re
2:09
both extremely important in industry. It’s just that connecting the two to each other is not that easy.
2:15
As a general rule, blockchains are expensive, the gas fees are expensive, and industry 4.0 has to do with
2:21
robotics. It has to do with basically uh individual IoT devices that they have to
2:26
be secure. they have to communicate just putting all these things together is just too expensive and that’s why it has
2:33
not been implemented yet. So why should they care about each other though each different domain or vertical
2:38
like blockchain people in industry 4.0 know people uh in from your perspective
2:43
give us two reasons why they should care about well you know when when blockchains came became of a thing right because of
2:50
Bitcoin uh because blockchains have been around forever it was really the the usage of crypto in blockchains that
2:57
became what we call blockchain today but the the promise of blockchain was actually industry 4.0 No, it was this
3:04
getting rid of this required trust that exists between people who produce products and people who actually use a
3:10
product. You want to make sure that what you produce is exactly what you’re
3:16
telling people. In other word, average customers, average uh users of products,
3:21
they really can’t don’t know the details of whether this thing is going to work for 5 years or for 10 years. They have
3:27
to trust. They need the trust to make sure that you did your job right. That’s the promise of blockchains when it comes
3:33
to manufacturing. So, so work agentic AI into this. Agentic AI is a new thing. It’s only
3:39
been around for about maybe a year and a half. Really started last year uh at the MIT Media Lab. That’s when it really
3:46
became big. But in a far in in in I think actually much faster than even in
3:51
the internet and maybe even faster than AI. Agentic AI become has become one of
3:57
the most important thing in AI because AI by itself uh is really just a tool
4:04
that people use for general everyday things. Yeah. But agentic AI is a specific function
4:09
that you can do with AI specifically to a specific task. Um so one of the things
4:15
that we’re doing at SQE is connecting Agent AI as an event generator or as a
4:21
uh basically uh as a as a sub routine that actually does something. So basically a task or the signal that
4:29
generates a task and is this where smart contract comes into play for SQE and can you explain
4:36
that if I’m on track? You definitely are on track. uh today as far as I know uh people are not really
4:43
bringing agenti into blockchains but that is exactly what we are going to do.
4:49
Uh so I realized the need for uh a new type of a smart contract like four years
4:55
ago I realized that solidity as it is is probably not going to be used for manufacturing and IoT applications. It
5:03
turned out that what I considered to be an event generator in for our SQ for our smart contract it
5:11
happened to be exactly the same as aentic AI. So we kind of like changed our frameworks and basically we call one
5:18
of the aspects of our event generators an agentic AI as an input to basically a
5:23
smart contract. So so now take us back to SQE. Why is SQE so ready to be a solution provider
5:32
here? So SQ stands for simulated quantum entanglement. So for those of you who
5:38
know what a quantum entanglement is, you realize that it is the most powerful tool in in physics. Uh it’s the part
5:45
that people don’t understand. It doesn’t make sense. Things that are not next to each other without internet that are
5:51
still connected to each other. and and the promise of quantum entanglement is what a quantum computer can do for you.
5:57
The beauty of SQE is that we can do that with using classical hardware. Um
6:02
basically this device right here has a chip in it and that chip actually does quantum entanglement. So we can bring it
6:09
down to a level where you can everyday IoT devices uh are can actually use uh
6:14
quantum communication. And now uh we actually going to showcase that today with two products that uh Jake uh Jake
6:22
Rush is in actually Rome. He’s our head of development. He actually has a couple of devices.
6:28
He’s in Rome today and as part of the demo coming up. Exactly. Okay. Great. So he’ll be demo of that. He will be showcasing.
6:33
Well I don’t want to get in the way of anything but I am interested for manufacturers listening um in particular
6:41
you know two things. one is you know what is SQE trying to get across in this
6:47
upcoming demo and if I’m a manufacturer how do I get started today
6:53
um so first of all SQ if that’s possible yes yes absolutely um SQE is trying to
6:59
basically create trustless trust okay in manufacturing uh by
7:04
explain explain that a little bit so essentially we have a device we call the Q IoT and a Q interface uh they’re
7:11
lowcost devices And they will be no low no cost low cost low cost okay just double checking
7:17
low cost devices and what they do is essentially you can connect them to any data acquisition system and essentially
7:24
makes them quantum proof uh meaning that nobody can ever hack them period in fact
7:30
are more secure than quantum and this is patented technologies this is a patent technology our patent finally went through after three and a
7:36
half years yeah congratulations congratulations so getting started is something that if
7:43
people see the demo and they want to get started, they can touch base with SQE and get in some sort of queue at SQE.
7:50
Absolutely. Okay. All right. Well, listen, I think it’s on to the demonstration. I appreciate you being here, Ham.
7:56
Thank you. Thank you, Dr. Thank you so much. Thank you for big for supporting us for the last couple of years.
8:01
Absolutely. We’re thrilled to have you as a member, as an S2A graduate, and and also for playing with our manufacturing
8:06
academy as you bring this manufacturing uh to to the surface. So off to the off
8:11
to the demo component. So we have a couple of hundred people online right now and uh from around the world and
8:17
they’ll take it from Rome I guess here. Is that Yes. Okay. Great. Excellent. Thank you. So Jake, you want to uh share
8:24
your screen? Absolutely.
8:29
All right. Thank you everyone. Uh my name is Jake
8:36
Ro, head of development here at SQE. And as you can see here on the screen,
8:42
can you guys still see it? Yep, we got
8:47
There we go. There we go. All right. There we go. As you can see here, we have two windows
8:54
uh the left on the uh that are essentially describing our Qlink messenger control panel. And as Tama
9:00
touched on, we have two uh separate Q-link um messenger devices here uh that
9:08
essentially once they’re connected to the their Wi-Fi network uh that as you can see in the status two different
9:14
Wi-Fi networks uh they don’t have to be on the same local network once the user logs in they’ll be able to uh send
9:21
encrypted messages back and forth. And this entanglement that Hamid had just mentioned is possible in our QLink
9:28
messenger modules through the use of our Q chip. And so this demonstration is
9:33
going to show a side by side of the two windows of two different QLink messenger devices, two different users logging in
9:41
and then sending uh the secure communication uh back and forth. And we’ll be able to look at the encrypted
9:47
packets that are uh being transmitted as it’ll be displayed on the screen. uh and then be able to talk a little bit about
9:53
our IoT module as part of the Qsafe family and then we’ll dive into the
9:58
sandbox and actually see these events that were created in our blockchain viewer. So, as we get started here, it’s
10:05
uh B we have two users, Alice and Bob, that’ll be logging into their uh respective QLink messenger device. And
10:12
this is important because the SQE registration, as we’ll show in the sandbox, creates an SQD upon uh
10:19
creation. and that is linked to the user and allows for the any data and the
10:25
events and messages that they send and create to be linked to their account using our Cubverse which is our uh
10:31
vector secured vector database. Right now, as you can see on the left side, Alice is going to be sending a message
10:37
to Bob. It’s going to be a very short and sweet message, hello Bob. And what you’re going to see is even though the
10:43
message uh decrypted is just hello Bob and very small using SQE in the Q chip
10:49
we can create a packet that’s uh no less than a kilobyte long and that’s uh using
10:56
our bit level encryption in the application layer. So this go is in a rip and replace system as you’ll hear me
11:02
say a couple times. This is cohesive with the current TLS security standards.
11:07
On the right side, you can see a few different things here. On the bottom, inside the incoming messages, you can
11:12
see Bob’s uh QLink messenger device did successfully uh decrypt that packet we
11:19
sent on the left side that you see, the encrypted version. And that’s again made possible because the QIP is maintaining
11:25
entanglement with the SQE network and the other SQE uh hardware devices. In
11:30
this case, we have the two QLink messenger devices. And now Bob’s going to send a response message uh using a
11:38
simple example of eight consecutive zeros. And this is what this is to show our bit level encryption really in
11:44
action. Regardless of how many zeros this message was to be sent again, we
11:49
can scale this not just from sending a message but also sending files large amounts of data. If there’s consecutive
11:55
characters because of our uh encryption is happening is being applied to every single bit. Again, a minimum packet size
12:02
of 1 kilobyte. It allows for true randomness and true security being sent regardless of what the decrypted payload
12:08
looks like. And so you’ll see here that Bob sends the message. And then you can see the encrypted packet. And then you
12:15
can see the decrypted version on the bottom left where Alice uh Alice’s
12:20
device was able to uh decrypt what you see on the right and then display it for Alice to see. What you’re seeing here
12:28
with these encrypted packets is something similar to what you would see if you were to use a a tool uh called
12:33
Wireshark. So if the if these packets were sent over HTTP where no TLS was
12:39
involved and you were intercept that packet that was transmitted through across the internet, this is what you
12:45
would see the the encoded encrypted uh message. Again, this is uh not a rip and
12:50
replace system. So it’s very cohesive with the current TLS standards as well. And in the sandbox, we’ll be able to see
12:55
a visual of that layered approach. Now, the last aspect uh of this specific
13:01
QLink messenger uh device is also our QoT module. While this recording was
13:07
occurring, Bob also had a Q IoT module that is linked to his SQE user account.
13:13
And this is to show this uh which we’ll be able to see is the IoT events that were triggered um are also being sent uh
13:21
into the SQE network in a similar fashion where the Q chip is built into the IoT module. So that the the Q chip
13:28
is entangled with the SQE network or the IoT module as a whole is entangled with the SQE network because of the Q chip
13:35
and then we can uh securely communicate IoT events for instance critical temperature sensors, pressure gauges,
13:41
tank levels um any sort of event that is very common in IoT and manufacturing spaces uh can easily be securely
13:48
communicated to the SQ network and then stored on the blockchain for uh full traceability as we’ll get into
13:54
momentarily. So with that, we’ll transition over to the sandbox demo.
14:02
And so this is the S3 sandbox. Uh for those of you looking at it for the first time, uh we released our SQL back in
14:10
October uh with the idea in mind of giving anybody interested in uh the technology that we’re developing and
14:17
being able to see the features that in the platform and the use cases that SQE’s overall entanglement and
14:23
encryption uh be able to see it in real time, be able to explore it, see the encryption results, see how your browser
14:31
um can because it’s a web application, be able to see it entangle itself with the rest of the SQE network in real
14:38
time. And so what you’ll see here is someformational buttons when you go to the SQE sandbox in different pages. And
14:44
that’s where we give an overview of uh a lot of the different back what’s happening in the background. It gives
14:50
some educational content. Uh here we also um encourage you to check out
14:55
sq.io.io IO the website, but also we have some great educational content that do does some deep dives into specifics
15:02
that I’ll be talking about today at our YouTube channel sq_secure. As Dr. D and Hamid previously mentioned,
15:09
uh also if you have any questions uh or are interested, you can always get um started right away by contacting us
15:15
directly as well. So with that, we’ll go into the uh exploring the SQE sandbox.
15:22
And what you’ll notice uh first here as we um enter it that there’s a the
15:28
registration and login page. What you’re going to notice here in our SQB sandbox
15:33
is a few different things especially when it comes to the registration and login. You’re going to notice there’s no
15:38
password input when it comes to registration and login. And that is uh on purpose because we are use we have a
15:45
zero knowledge keypad uh that is a tool that we use in order to use zero knowledge principles in order to log you
15:52
in and verify you as a user which we’ll get into uh momentarily. But then you’re
15:57
also going to see two sections as a part of this registration. The top part being uh the required information. A username
16:04
that hasn’t that doesn’t exist yet an email first and last name. Ultimately the email gives us a multi multiffactor
16:11
authentication to send you a PIN as the uh mult the zero knowledge keypad is in
16:17
its early prototype prototype stages and is a one of many uh aspects that we use
16:22
to verify you as a user. But also the bottom half where you see the date of birth some more personal information is
16:28
to demonstrate to you what our SQI SQD does when you register an account. So
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every time you register or when you register uh an account with SQE, we have
16:40
a decentralized process that creates a 1,024bit SQD. And that SQID is uniquely created
16:48
and linked to your user account. And it’s based on the personal information
16:53
that you have um you you’ve sent in upon your registration. And this SQID is used
16:59
in m multiple different ways ranging from permissions um as you’ll see with the blockchain viewer and then also it
17:06
contributes to the long-term uh encryption and decryption storing mechanism that we have on our database
17:12
and within blocks on our blockchain that so that means all the information that is yours or that you have access to
17:19
because multiple users can u be a part of say a transaction uh that SQID is one
17:24
of the foundational tools used to allow you to actually encrypt and decrypt your
17:29
own information so that nobody else can that doesn’t have your SQD and and your attributes and and and whatnot. And so
17:37
with this, we’re also going to, if you uh remember from the QLink Messenger demo, one of the accounts that logged in
17:43
was Bob. We are going uh going to see that Bob is going to log in uh into his
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SQC sandbox and we’re going to be able to um explore the different use cases and see the different events that were
17:55
generated previously as well. Right now Bob has clicked uh entered his username.
18:00
He didn’t enter a password and now he’s in the uh our zero knowledge keypad stage. And this zero knowledge keypad as
18:08
I previously mentioned has uh two aspects. one, it’s uh a contributing it’s a tool
18:14
to contribute to uh verifying you as a user, but also it’s what initializes the
18:21
entanglement in real time for your active session with the SQE network. So by inputting the PIN you receive uh
18:28
through your email. That’s one of the many aspects we use to verify you as your user account. But then also that
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PIN is used using zero knowledge principles to be able to entangle yourself without the need of a public
18:40
private key exchange to entangle yourself with the SQ network. And so therefore everything you’ll see once
18:46
we’re entangled everything going forward is using this application layer encryption that you just witnessed with
18:52
the QLink messenger. So because your web app doesn’t have the Q chip like the hardware device does, the zero knowledge
18:58
keypad replaces what the Q chip does to initiate uh entanglement. So you’ll see every few seconds here um
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the keypad will regenerate and then it’ll um it’ll be stable once the user
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begins entering his PIN. And you’ll see here that now Bob enters his uh his his
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unique PIN for the account. And now we’re entangled. We’re logged in. And now we are brought to the SQE sandbox
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overview page. So you’re going to see a few different things here in the SQE sandbox overview page. The first being
19:31
in the top uh left right around the welcome, you’re going to see abbreviate the abbreviated unique SQID that’s
19:38
tailored to Bob. Uh it’s important to note that these SQIDs are not just limited to linking a user SQ user
19:46
account, but it’s als there’s many types of SQIDs. SQIDs can be tailored uniquely to assets. They can be tailored to
19:52
organizations and companies as well as uh devices that are registered within the SQ. Uh, for example, each QLink
20:00
messenger, Qiot device, they all have their own SQD that’s registered and
20:06
uniquely tailored to that device. Um, and it’s authenticated in the SQE network. You can also see that the
20:12
account balance for our simulated payment use case. And then you can see the different modules that we have uh
20:18
currently on the SQE sandbox. This includes our encrypted messaging, our ISO standard uh 222 payments and then
20:26
our new uh upcoming release which we’ll be able to show you guys today, the blockchain viewer. We also have our
20:32
tools and utilities that describe uh differentformational aspects uh like for
20:37
instance how the SQE application layer um it fits in with the TL TLS layer um
20:44
and whatnot and we’ll go over that uh momentarily. So right now Bob is going to show the uh secure messaging use case
20:52
specifically. Uh right now there’s no active users on the network and so there’s no worries when you expose
20:57
sandbox if no one’s online you’re uh you can test the secure messagings and secure payments with virtual users. So
21:05
right now Bob is going to send a secure message to uh virtual Alice and it’s
21:11
going to be very similar to what we showed with the QLink messenger. send a message hello Alice and then we’ll be
21:17
able to see the uh in the conversation history uh two aspects uh once we see
21:22
the message we can see the decrypted version and then the encrypted version in a slightly different format um again
21:29
every the minimum packet size because SQE doesn’t uh require the public private key exchange our encryption keys
21:37
uh can be quite large right and so that allows us to have um a packet size that’s at least a minimum of 1 kilobyte
21:44
And that scales as data that needs to get sent over the internet grows, right? For example, files. But you can also see
21:50
the hex values and the randomness that happens within these encrypted uh encrypted packets that are leaving your
21:56
browser being sent to the SQE network. And because that secure channel is established that was initialized by the
22:03
keypad, uh the network can uh decrypt that packet or route it in this case to
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the receiver and then um send a response back. So now you’ll see the new use case here
22:16
that we’ve added to our messaging which is our store on the blockchain portion specifically. Um now everything is tied
22:23
to this SQD and this user account. Now when we send a message um and we want to
22:28
store it on the blockchain it’s going to generate an event or an a transaction
22:33
that gets stored um in our cubverse specifically our decentralized link and
22:38
node system that’s creating a block. What you can see here is once we sent the message, we now have an onch onchain
22:45
tag uh with a block ID that’s associated with the transa with the message that was uh sent to virtual Alice. And then
22:52
we have our decrypted message and then encrypted version uh to be able to look at as well. This block ID uh we’ll be
22:59
able to reference later on when we look at the blockchain viewer. So now that the last example uh we’re
23:07
going to go through here with our secure messaging is to really uh show the uh
23:12
how our entanglement works and how it evolves over time. Um as we showed prior, we did eight consecutive zeros
23:19
and that showed our bit level encryption um and how it our messages are still secure with consecutive characters. But
23:26
now we’re also going to see how the packets look when we send the same message twice. And because uh the
23:33
entanglement and the particles that are used to entangle the SQE network or the other devices to the browser um we can
23:41
see that they’re evolving rapidly over time. And that allows for your packets to be secure even if you’re sending
23:47
repeated me packets or repeated structured packets. No encrypted packet ever gets repeated. And again that
23:54
minimum packet size of 1 kilobyte even if the packet uh the decrypted payloads are small.
24:00
And so we can see here the encrypted versions are completely different uh random hex values. There’s no repeat.
24:06
And again because it’s evolving so quickly, we can send messages uh very quickly without any repeats as well. Now
24:13
we’ll transition into our simulated payment. Everything uh every payment that gets sent is going to get stored on
24:20
our blockchain uh which will be able to see the block ID and and map that in our blockchain viewer. Uh in this example,
24:27
Bob’s going to send a $150 payment to virtual Charlie. And then we’ll be able
24:33
to also see how SQ’s application because it’s in the application layer, it doesn’t get affected by current uh
24:40
compliance and um structures like for instance the ISO standard. Um SQE is uh
24:46
is acknowledging the uh current compliance standards that are here today
24:51
and implementing them. but also for companies that already have the sock 2 and the ISO compliance because we wrap
24:59
around the data the encryption data structure which we’ll see in our um where it fits in the application TLS
25:06
layer um we can still see the packets encrypted and you can see all the controls with this simulated ISO 222
25:13
payment and then you can also see the encrypted payload that gets wrapped around uh the the initial payload to
25:20
begin the payment process and Then you can see all the ids and the full traceability. It’s also important to
25:27
note that the full trace this the blockchain uh SQ SQE has where these uh
25:32
events get generated uh get stored one transaction per block. And so that gives
25:38
all these events that are generated within for instance a payment to be able to be fully traceable um through the SQE
25:45
blockchain and fully secured based on our secure storage mechanism thanks to our SQIDs.
25:53
And so now we’re going to just uh take a quick look at reminder of that block ID 715 ends with a E2 and we can map that
26:00
to our blockchain viewer. So now we have we’re here on our blockchain viewer.
26:06
What you’re looking at here is the blockchain viewer where we can see the blocks on the master blockchain that
26:11
have been generated. But a little overview on our SQE blockchain. SQE is a
26:16
layer 1 blockchain. It’s not just a ledger, but a real-time system designed for high frequency and industrial and
26:23
for industrial-grade data. Unlike traditional blockchains that batch transactions together, SQ’s blockchain
26:29
stores exactly one transaction per block. This gives you full traceability at the atomic level in a manufacturing
26:37
environment. That means every sensor reading, every machine event, every action and is independently verifiable.
26:44
If a defect shows up on a production line, you can trace it back to the exact event that a batch then say a batch of
26:50
500 mixed transactions under the hood. This is made possible because the blockchain is powered by our
26:56
decentralized link and node architecture that utilizes SQE’s secure communication
27:01
and storage thanks to our our cubverse vector database. Each block is independently secured and distributed
27:08
across nodes. So there’s no single point of failure and no decentralized or no centralized trust dependency. This is
27:14
especially critical in industry 4.0 where devices, factories, and partners are all interacting across different
27:20
networks. Because the blocks are independent and not batched, we can process transactions in parallel. This
27:26
means the system scales linearly as more nodes are added to the network. So whether you have a device or 10 devices
27:33
or 10 millions sensors streaming data, the system doesn’t bottleneck.
27:38
Additionally, it’s important to uh make note of the blockchain’s efficiency. Traditional blockchains are expensive
27:44
because of compute heavy consensus mechanisms that Hamid touched on earlier uh in this uh demonstration. Our model
27:52
minimizes the energy required per transaction which drives the cost down significantly making it viable for high
27:58
volume environments like IoT where you might be generating thousands of events per second. Ultimately this enables SQ’s
28:05
blockchain system to not just be secure but actually usable uh on an industrial
28:11
scale. High volume, low cost, and full traceability is is kind of the key here.
28:16
And so now we’ll dive into the different components of the blockchain viewer. You can see and we’ll be able to see and map
28:22
the different events that Bob had uh Bob’s events that he generated uh previously in this demo. So you can see
28:29
here we have a few different columns on the blockchain viewer. The first being uh the block number, the block ID, all
28:36
the block ids are unique to that specific block. And then you can see the SQD that u the source SQD that
28:43
initialized or initiated that transaction or event. You can see we have a few different types of events.
28:48
the payment, the send message, the IoT, uh, and the different Q-link messages also. And then on the right, we can see
28:56
the access and whether and you can see there’s quite a few that, um, that Bob has created recently. And then you can
29:03
also see the restricted where other users that he does not have access to, but again founding on his SQD. Uh, so he
29:11
can’t see the private information and he wouldn’t be able to decrypt that block e anyways.
29:17
So now when we apply this blockchain to the IoT, we can see here the block data.
29:22
We can see the block structure on the block inspector because he owns that block or has been granted access to that
29:28
block. Um specifically we can see the um the payload hash, the different hashes
29:35
and then most importantly we can see the the the IoT use case, the control room urgent. And so as Hamida had talked um a
29:42
little bit before this, this is where the smart contracts will then come in. These are the generated events. The
29:48
smart contract can also then uh perform actions based on the events that are stored in the blockchain. And then our
29:54
blockchain allows full traceability um as it’s stored. And then lastly, we can
30:00
see when we try to access a restricted event, we’re unable to we’re unable to decrypt it. It’s fully secure on our
30:06
blockchain and within which is within our cubverse. And then the last thing here, we can see
30:12
the uh payment. We can see the payment we just created. Our block ID matches up with the block ID that we saw previously
30:19
in the payment section. And we can also see that there’s a few different things
30:24
that we can do. We can sort and view the different blocks. Uh we can see the different types. And then this as more
30:31
events get generated the master blockchain will grow and there’ll be more access to seeing uh more blocks and
30:37
events. Fi lastly we have our different utilities. Um we highly recommend
30:44
checking these out and learning more about where SQE’s application layer uh encryption lands in the full stack or
30:50
the OSI model. Uh we can see the TLS is just a one layer. It’s not a rip and
30:56
replace. Um, with the idea of harvest now decrypt later, uh, SQE’s encryption
31:02
in the application layer adds as another protection, another shield against that harvest now decrypt later. We also have
31:10
our compliance mapper uh, where you can see how we fit into the different compliances like KYC, secure messaging,
31:17
ISO 222 payments and how our encryption fits into those compliances. And then
31:23
finally, we have our NRA scale. Uh feel free to check out this link where you can get your free risk assessment um
31:29
which is powered by Netroscale. And that’s uh all I have for you today. Thank you everyone for your time. And
31:35
again, if you have any questions, please reach out to the SQE team to get started.
31:41
Can they hear me? They they can hear you. So thank thank you Jake. That was great. Um amazing. I hope you’re enjoying your
31:48
vacation in Rome. Jake Jake is actually lives in Massachusetts. He’s a Massachusetts guy.
31:53
Yeah, he’s in Worster area and he’s vacationing and originally we were
31:58
supposed to have this meeting last month. So, he’s dedicated hand. Yeah, absolutely. No doubt about it.
32:05
He’s a gold mine that he just happened to find. Um, uh, Jake showed quite a few things.
32:10
Uh, I just want to add a couple of notes to that. Um, one thing that he showed was how
32:15
fast we are encrypting. I just need to uh let you guys know that the level our level of encryption is beyond any
32:22
quantum computer. In fact, it takes more energy to decrypt one of our keys if you
32:28
don’t have the key than that actually exists on a planet Earth. It’s virtually impossible. It’s uh our uh key
32:36
encryption keys are not 256 bed or in this case he was showing 8,192
32:42
bits. If you have a 1 megabit file, you get 1 million bits of encryption. We can
32:47
show that we can generate 7 billion bits per second on a standard server. So on
32:53
real on a standard server, what’s that? On a standard on a standard server. Nothing. In fact, on this laptop, I’ve tested 7.2 billion
33:00
bits per second. Okay, that’s faster than any other encryption methodology, even with hardware
33:06
acceleration. Having said that our random number generator which we’ll have ready within next four weeks it’s a
33:13
service initially free uh you can generate your own random number. We are actually showing that we have a higher
33:19
entropy than quantum computers. you cannot generate this level of entropy and I don’t think we have the right
33:26
setting to tell you how is it that we can actually generate higher entropy but anybody who’s interested we can set up a
33:32
medium we can show you that we have the results that is measured by uh NIS standard 800B we can show you that we
33:39
have a higher standard than even the highest setting that uh even NSA uses um
33:45
and there is a reason for it I spent a long time trying to figure out how is it possible you’re creating more randomness
33:51
and the quantum nature of universe and I found out why and I can tell you why but it’s probably not the right study right
33:57
now. That’s great. Great control by the way because normally when I’d have a coffee with you, you would tell me why.
34:04
So Hannah, I just want to just uh bring this up because I think it’s important getting somebody who’s like a theoretical mind like yours and a
34:11
creative inventive inventive visionary um to then make something practical that
34:17
actually can be conveyed by uh a person from the Commonwealth from Wester area
34:23
while he’s in Rome. it it actually makes sense to look at the dashboard and follow along is a tremendous feat based
34:30
on where we started our conversation years ago. Yeah. Um so you know sometimes I know what
34:37
you’re up to but just to see it transform into this kind of event that
34:42
gets me even to think how can I use this technology in my own life even with a
34:47
smaller enterprise. Um it it’s really encouraging. Yeah. So I have here um I’m not sure if
34:54
everyone sees us. Uh yes, they can see us now. These are this is what Jake has in his
35:00
hand. Uh this is our prototypes of Q link. This is a device that you will connect to your own uh business or home
35:07
network and any uh so we have an application just make sure you’re speaking to the mic as you’re saying.
35:13
So we have an application that you basically access through your mobile phone. Your mobile phone gets connected
35:18
to this device. any messages sent through this device is 100% quantum proof. So that’s our what we call Q link
35:26
and people could get that uh you can actually sign up to get it. We are in you’re on a waiting list kind of thing.
35:32
We kind of like have a waiting list right now. We we will be basically releasing about 200 of them uh by the
35:39
end of uh beginning of May. Okay. Uh maybe midmay. So you can sign up to get one. Uh uh this we haven’t set a
35:46
price for it, but it’s definitely sub $100. Um this is what I call Q secure.
35:52
I’m sorry, Q wallet. Q wallet is a device that you can connect to your laptop and you can keep any secret, any
35:59
password from any application, including all of your blockchain uh addresses that
36:04
you might have. This is practically quantum proof. uh even if you lose this
36:10
device, we can recreate it for you because all the information is backed up in Cubver and only you have access to
36:17
- So the way to access it, there’s no password. You plug it in, you get on
36:22
your phone, you basically the fact that you got on your phone enables it. So you have access to the data. Uh if you lose
36:30
this, we can log you in through your data, you can register and we will make another one just like that copy for you.
36:36
Um, again, we don’t have a price setting for this. This will probably re be released uh in in um uh July, something
36:44
maybe July, August. But uh uh there’s several other products that No, I’m getting we got one more one more
36:51
product offering and then we we have two products here that the actual first IoT devices that have the Q
36:58
chip in them. And with that, I’m going to Okay, great. Now, we’re going to open it up for questions, I believe. Is that
37:04
correct panel? Okay. Thank you.
37:10
Great. Thank you. Thank you so much everyone. Um uh thanks Hamid, Dr. Dennis
37:15
and Jake for getting the session going. Um so we talked about manufacturing. Uh
37:21
we’ve talked about identici uh blockchain technologies. Um the panel
37:26
discussion we’re going to kind of delve a bit deeper and think it think in terms of security and what the implications
37:31
are for the merging of these technology converging to create these amazing industry 4 uh solutions. Uh so we have a
37:39
fantastic panel today. Um I’m going to do let them do a quick introduction then we’ll get going. Uh first of all Sarah
37:45
if you don’t mind do a quick introduction. Sure. Um hello everyone. Uh my name is
37:51
Sarah Sari. I’m associate professor at uh Worcester Politic Institute um at
37:57
Worcester in Massachusetts and my main research area is in supply chain management operations and blockchain and
38:04
very honored to be part of this team and to be here with you guys.
38:10
Thank you Sarah. Uh Richard Moore please. Hi everybody. Richard Moore uh I am the
38:17
CEO of Cyber 6. I’m also from Worester. Uh so again got this nice tiein for the
38:24
uh local communities and I am an adviser for cyber security for SQE. So thank you.
38:30
Thanks Richard. Andwise
38:37
I don’t see my content. No. Okay. Uh okay. And do we have Nick
38:43
Gibbs? Nicholas. Okay.
38:49
Hi Dennis. Hi. Uh I hope you can hear me. Um my name’s Nicholas Gibbs. Um yeah, so I’m not quite as intelligent as
38:55
the rest of the panel here. Uh we we build data infrastructure uh across the EMA and uh we also deploy uh private
39:02
networks. Um, a bit of background, we we built a blockchain um uh crowdfunding uh
39:09
uh project with and we we got the SQE support when I first met the guys a few years back now um for for impoverished
39:17
communities to be able to fund their own critical data infrastructure at the edge. Um so obviously as we move into
39:22
this uh IoT world and the and industry 4.0 know, you know, the the edge becomes
39:27
a a critical component and uh and we feel that as as some of the we’re not
39:32
looking at hypers scales here on the tier ones, but but as we look outside of tier ones and we look into the to the second and secondary and tertiary
39:38
markets where where where data is going to become even more um a scarce resource um then uh then then we we feel like
39:45
projects like SQE can really help to to to support that move. Thank you, Nicholas. Great to have you
39:50
here. Okay, great. Okay, we’re going to go with the first question. Uh the first question is for Sarah please. Uh so
39:56
Sarah um we hear a lot about industry 4, smart factories, connected supply chains, machine talk to machines. For
40:04
the leaders watching today, what does this actually look like on the ground and why does it create new security
40:10
challenges that older approaches simply weren’t built for? Um thank you Dennis for this question.
40:17
So um let me define I know maybe um it’s familiar but I would like to just very
40:23
um quickly review the the industry 4.0 going to open supply chain management and manufacturing. And um this is
40:30
something that is that involves the collective implementation of uh disruptive technologies that we have
40:37
including for example augmented reality, artificial intelligence, cloud computing, blockchain, internet of
40:43
things that they like to work across the network value of our product or products
40:50
in the supply chain. And this is exactly where the machines, computers and even
40:55
human work together in today’s factories to form the cyber physical integration
41:00
that we are all talking about. And let me give you a few example. The real example that we do have in reality in
41:06
manufacturing for example Bosch um automative Bosch in China they use
41:11
sensors on their machine to collect data in real time so that they can predict
41:16
using AI algorithm they can predict the machine failure time and could fix it
41:23
before it happens and that increased their production by about 10%. That is
41:28
huge in um in a production um um perspective from production perspective
41:34
or for example in Netherland um DHL they use mobile robots that they exactly work
41:41
alongside with people there in um in warehouses to just find out the best and
41:47
optimum route and path in the warehouse to move and transfer the the packages.
41:53
And you know time is something that is very critical in shipping industry and
41:58
they could reduce it by 50%. huge huge kind of like improvement. or
42:04
another one just like BMW that um they use digital twins and call a um platform
42:11
like iFactory uh for uh over 30 plus sites of their um production to
42:18
specifically simulate the collision checks because it was done previously um
42:24
using physical like equipment um about four weeks for their new vehicle models
42:30
but now they could reduce it by simulation to 3 to 4 days and reducing
42:36
the cost by 30%. And this is what we call operational resilience from supply
42:42
chain perspective. And this is where we say this is hyperconnected reality that every sensors, every robot, everyone are
42:51
um even in the the in the like delivery truck they are sharing the data and huge
42:57
data at the same time that they should also talk and decide and um checks
43:03
everything in real time. So here when we’re talking about blockchain um sorry
43:09
the supply chain for 30 years we thought that if machines are not going to be
43:15
connected to internet they’re going to be safe but it’s not the case anymore we need access real time because we are
43:23
going to connected to the cloud computer we are going to use AI um to just u like
43:29
predict everything so in that perspect think we are talking about other
43:34
security that might um that we might have um for example it’s about the
43:41
uptime priority uptime priority is really important when we are in the
43:47
manufacturing perspective in IT when you reboot a system it might work or restart
43:52
it or reinstall it but it’s not possible for operations um word by rebooting a
43:59
for example highspeed assembly time, you know, uptime is a scared and um um and
44:05
we often need to um or we can’t actually afford a downtime easily. The other
44:12
things that we have uh it’s about legacy system.
44:17
I’m not talking about very high advanced factories but generally so far at least we have many companies that are working
44:23
with legacy system that even they were produced before we have the word of cyber security. Yeah. Um and we need the
44:32
system so that they can talk with these legacy system. And finally we have and
44:38
other things that we call it like blast radius. It means the the connection that we do have with the sensors with the
44:44
machines everything that um are here in our um network or um cyber physical
44:50
network um that because they are so much connected. one um small poison poisoning
44:57
or one of them that might be poisoned it can exactly um like um target and
45:05
transfer it to the whole system and we kind of coming up with a catastrophic
45:10
decision like shutting down a healthy system. Um so the challenges that we
45:16
have in these very interconnected um uh like manufacturing or industry 4.0
45:23
that we are seeing it can be related to data fragmentation interoperatability that we need to have the system to work
45:30
and to talk and to translate the data so that they can work with together. We
45:36
need to have adaptation for workforce. The human resources they need to be adapted so that they can use these
45:42
technologies efficiently and don’t think that they’re going to replacing them totally. On top of the cost of
45:48
adaptation that are millions of dollars um specifically for like full implementation,
45:55
we have concerns about trust, cyber security risks, transparency and
46:00
accountability because generally AI systems or those systems that are like deep learning um unsupervised um like um
46:08
learning they use as a black box and it’s difficult to know what how we how we should interpret their decision and
46:15
it’s all the problems that we do have in operations and supply chain that we
46:21
really need to think of trust and security at this point for these systems.
46:28
Thank you Sarah. Um big takeaway for me there is um it’s quite clear that in these hyperconnected environments
46:34
traditional security simply doesn’t apply you know. So uh in fact that’s a nice segue to the next question I have
46:40
for you Sarah which is um so AI is now making real-time decisions inside factories and supply chains. We talked
46:46
about that, right? Uh we’re rerouting shipments, flagging faults, adjusting production. When those decisions are
46:52
made by a machine rather than the human, how do we know we can trust them? And what happens when that trust is
46:58
compromised? Sorry. So um that’s another thing that I
47:06
wanted to introduce um to talk about um moving from industry 4.0 toward a human
47:12
centric vision of industry 5.0 O which we are now emphasizing on the resilience
47:18
ethical governance and the collaboration that we have between human and machine and that’s the place that we are um like
47:26
talking or or introducing agenting AI that stands at this intersection how we
47:31
define it we define them as a digital like full-time equivalent of of systems
47:37
that are capable of negotiating deciding and acting in a complex environment that
47:42
we don’t need human intervent vention. So for example in a manufacturing setting we can say it can be kind of
47:48
like a rroot of shipments during disruption or rebalance of stock across
47:54
few regions based on the demand that they are seeing or the demand pattern
47:59
that they saw um through the previous times for example the previous week and even negotiating some kind of like new
48:06
terms with supplier according to the situation that they have uh as a geopolitics that is changing for example
48:13
we have Amazon on project Aluna that they use agentic foresight to and to
48:18
kind of predict the bottleneck and keep the operation running um smoothly as
48:24
possible by having or integrating kind of historical and real-time data. And
48:30
that’s how they actually changed the meaning of resilience from extra stock
48:36
in the past in the warehouse to the resilience that we we need to know about
48:41
the speed and adaptation. And when it’s speed and adaptation
48:47
um so it’s it’s different um we need to consider other things because as I
48:52
mentioned we have many interconnected um like devices for example here with
48:58
agentic AI we assume that if a supplier fails we assume that our agentic AI
49:04
would help us to find a very good suitable new supplier but the big question that we have is that how we can
49:11
trust the data that these AI I received and act upon what happened when this
49:18
trust is compromised and um how we should uh look into that. So when the
49:23
trust is compromised the first thing is that we will have like a cascading
49:28
failure. Yeah. If a sourcing agent makes an error and it feeds that context to
49:34
the logistic agent and then it execute a flawed physical action. So it would have
49:40
cascading events and it’s not only that cascade um it’s it can be kind of like
49:46
coordinated deception throughout the whole system and that’s why we kind of coming up with a systemwide
49:53
systemwide catastrophes and and it also impact the memory of the
49:59
agents that would impact the future uh uh like uh action. And finally um we get
50:07
to the situation that resilience changed the myth. We don’t know what exactly we should do. And in that perspective
50:14
um I think we we should rely on two new technologies that are very um like
50:20
promising in closing these gaps or at least decreasing it decreasing these
50:26
gaps significantly. One of them is blockchain that is something that I am working with a lot and the other is
50:31
quantum ready security. And let me explain why. Well, when it’s blockchain, we cannot um
50:40
because we can’t see exactly what is the AI brain as I mentioned is a black box.
50:45
We need an unchangeable record of the data that AI used and who did their
50:52
action that they took. So a permission blockchain exactly provide that that
50:58
every sensor uh reading and every AI command can be exactly readen as a
51:03
transaction recorded and cannot be altered. Even a smart contract on blockchain can automatically check for
51:10
example if the maintenance order was exactly somehow issued when uh we had
51:16
like a right threshold for that product for example and it can help us for
51:22
checking and confirmation in the whole system. But at the same time when we are talking
51:28
blockchain we are very concerned nowadays about the authenticity of uh
51:33
the the data that we are going to put on this blockchain against the future threat because we know that quantum
51:39
computers could break these encryption today that we use for uh protecting
51:45
data. So in that perspective it mean it means that we need to use somehow
51:51
quantum resistance cryptography that they use those um exactly um quantum um
51:58
system in order to encrypt and therefore we just use the same kind of like um or
52:05
the similar um algorithm so that we can make sure the data is safe. So for
52:12
supply chain expert I would say ensuring that the blockchain and hardware security infrastructure is quantum
52:19
resilient. It’s a critical thing in the long-term um operational integrity and I
52:26
I’m here to just hear that I mean I’m I’m here to say that SQE is a technology
52:32
that offer both things a blockchain in a quantum um resistance with quantum
52:38
resistant cryptography and something that is ready for manufacturers for plants and for supply chain management.
52:46
Amazing. So important. Thank you Sarah. very interesting uh context there and um it’s
52:51
a nice um opportunity to kind of delve more broadly right it’s got other critical industries as well uh so rich
52:58
with your help um at cyber 6 you see attacks playing out in real time um from
53:03
your security operations center are there threats happening today this is before quantum computers even exist
53:10
because we know innovations moving rapidly but they don’t yet they’re not commercially available right now um that
53:16
already exploiting the gaps in how you authenticate machines and protect operational data. So any threats
53:22
happening today uh that you mentioned. Yes, Dennis. Uh you know the
53:27
uncomfortable truth is that many of the most dangerous threats today have nothing to do with quantum computers. Um
53:33
they exploit gaps in machine identities. Uh they take advantage of weak or
53:38
missing authentication between systems and of course the poor protection of operational data data. These attacks are
53:45
accelerating because AI is making them faster and easier to execute. Right? So
53:50
if we break it down when we talk about the exploitation of missing or weak uh
53:55
machine authentication, basically what we’re saying is most organizations do a really good job to authenticate the
54:02
user. However, they do a really poor job of authenticating the machines. And this
54:08
gap is being already weaponized by malicious individuals. uh it’s something that we need to think about and if we
54:15
move on to the next thing this vulnerability discovery as we already talked about AI is doing a great job at
54:21
helping us correlate all kinds of data but it’s also taking advantage of
54:27
identifying weaknesses within systems automatically deploying uh an attack
54:32
vector into that uh vulnerability and again this is making it so much easier
54:38
to attack without any quantum computers because it’s identified ifying large amounts of data which is it’s really
54:44
good at doing uh and then exploiting that particular weakness. I also mentioned the compromise of machine
54:50
credentials, right? So, we’re using API keys, we’re using tokens, we’re using service accounts to manage these
54:56
machines. That machine identity is already a mainstream attack vector, right? So,
55:03
folks are already using it. Most organizations don’t monitor machine credentials as rigorously as they do the
55:10
human ones. And and that’s what we’re seeing out there uh in the sock. We’re seeing lots of machines uh basically not
55:17
authenticating properly, machines being used by accounts, by APIs, by token
55:22
failures, etc. And now we talk about we take that and we take those machines,
55:29
those APIs, connectors, and now we’re really talking about a supply chain and SAS integration attack, right? So
55:36
operational data has to flow through these integrations. uh if the machine trust model is weak, then attackers can
55:43
silently manipulate or siphon data off of these uh machines and and therefore
55:48
you’re putting not only your supply chain, your third party uh but anything that’s uh trustworthy, meaning as Sarah
55:55
mentioned, the integrity of that data, whether you’re controlling a uh uh an
56:00
oven or controlling a robot or you’re controlling some manipulation of of a
56:06
utilities group. uh all of that data is valuable at some point to be able to
56:12
make an attack. Um so when we talk about that and uh we we had this conversation
56:18
of harvest now exploit later uh this is the operational data manipulation. This
56:24
is perfect. So I’m going to gather all this data. I’m going to try to uh break the integrity of it. I’m going to uh
56:31
steal its confidentiality and I’m going to use that data for future use. It may not be right now, but
56:38
somewhere down the road, I’m going to get that patterns set up. I’m going to understand how uh I can potentially
56:44
break current uh postquantum algorithms uh because that’s fairly easy today. And
56:50
we’re going to think about how we’re going to, you know, break into banking or manipulate your keys or or something
56:56
down the line. So, these are things that uh the patterns are emerging from the
57:03
sock, right? So again, we’re talking about weak machine identity, missing authentication between systems,
57:10
unprotected operational data, and not yet from a quantum machine. But when quantum comes, it’s going to break it.
57:16
Uh that’s why this SQE entanglement is so valuable. When you hear Hamid talking
57:22
about you know protecting the OT devices, protecting the way in which uh communications happens, this is what
57:30
every security operations personnel, every security professional should be thinking of. Not a modulized solution,
57:37
but something that can break these patterns of attacks. I hope that answered your question, Dennis.
57:44
Absolutely. Yeah, thank you, Rich. uh so important because I’m glad you touched on the hardware and security aspect
57:49
because tell you what I mean and team have done is to deliver something that’s truly unique reduce your attack surface
57:55
let’s not think in traditional uh terms and it took someone from outside cyber to come and innovate you know so really
58:02
excited to be working with the SQE team um rich I have another question for you uh which is so as security as the
58:08
security landscape evolves how should the role of the security operations center change so what does this look
58:13
like when it comes to things like monitor ing and defending a world where AI agents are making decisions and data
58:19
flows are protected by blockchain. Yeah, great question on this one, Dennis. Uh again, the security
58:26
operations concept of the future, right, must become trust verification and
58:33
autonomy governance center, not just an alert handling team. That is a big difference, right? So when we think of
58:39
the world of AI, blockchain secured data flows, the sock shifts from chasing alerts to governing autonomous systems,
58:47
validating machine decisions, enforcing cryptographic trusts, and monitoring the
58:52
decentralized data integrity. The AI handles detection, humans handle oversight, adjudication, and safety. And
58:58
I think that’s a great uh, you know, addition to what Sarah was mentioning. Uh so so now we’re changing from these
59:06
alert responders to what I just called the governors of autonomous security system. So kind of like this is the
59:13
human in the loop. This is where we set policy boundaries. Again I think Sarah
59:18
and Hamid had talked about smart contracts. How can we leverage that to help enforce policies and boundaries? Uh
59:25
we’re talking about reproving or rejecting high impact automated actions.
59:31
And the really interesting part is monitoring that AI drift, whether it be hallucinations or unsafe behaviors. Uh,
59:38
you know, again, if we’re thinking about training our models, we want to make sure that the data going in is good data
59:45
uh and that we’re we’re not putting in, you know, destroy the universe type uh queries. So, we want to make sure those
59:52
things are are happening. And that’s a that could be the sock of the future’s job. uh we moved from log analytics to uh
1:00:00
cryptographic verification. So again blockchain introduces that immunable decentralized event log. Again very
1:00:07
important uh we now got to verify the integrity of using blockchain proofs. We’re monitoring the smart uh smart
1:00:14
contract based security controls. We’re you know detecting attempts to bypass or
1:00:20
poison the ledger which Sarah had already mentioned as well. And we’re thinking about using blockchain for
1:00:25
tamperproof incident timelines. Again, as we all have seen in the news, you
1:00:31
know, organizations call in forensics. Uh somebody from the executive staff
1:00:37
walks in and uh basically says something that’s not necessarily true yet, and now
1:00:42
the company’s reputation is put at risk at risk. So if we can use these tamperproof incident timelines to help
1:00:50
drive the discussion that’s going to be very great for uh the future of a
1:00:56
security operation. We talked about human-driven triage, right? So we’re now
1:01:01
AIdriven threat prediction. So we’re correlating cross signals. We’re doing
1:01:06
identity endpoint SAS etc etc. We’re trying to predict attacks before they
1:01:12
mature. We’re reducing false positives and we’re autogenerating those incident reports. Right? So this now is a
1:01:19
strategic risk decisions not raw detection. And we’re moving from centralized monitoring to distributed
1:01:25
trust assurances. Right? So data integrity is guaranteed cryptographically. Providence becomes
1:01:31
traceable. Every transaction is auditable. Compromise requires consensus manipulation, not log tampering. Again,
1:01:38
we’re monitoring the health of the trust fabric, not just the system. And then
1:01:44
finally, from analyst fatigue to autonomous scale. Again, we already know that auto triage, auto investigation,
1:01:51
autocontainment, auto documentation becomes the sock’s quality control, not
1:01:56
a manual labor. Therefore, the sock really jumps forward to a control room
1:02:02
to monitoring for behavioral uh analytics not just for people but for
1:02:08
agents. Uh again, we’re talking about blockchains and then again AI first
1:02:13
incident response. That is the future of how we not only wrap uh the sock around
1:02:20
today’s current events, but we’re thinking about postquantum quantum world. This is how we have to do it.
1:02:28
Thank you, Rich. Um, that’s a really really good um entry point. So, so Rich and Sarah have given us an entry point
1:02:34
to help set the scene. Um, we’re going to go a bit deeper now with the help of Mike Wise and Nicholas Gibbs. Uh, here
1:02:41
we’re going to go a bit more into the technology, talk about scale and real world fit. Uh, so Mike, um, if you
1:02:47
wouldn’t mind, um, first question I have for you. Um, by the way, Mike, do you want to do a quick introduction because I think I missed you first time.
1:02:53
Yeah. Yeah. Sorry about that. I was I was on the attendee side and not the
1:02:58
panelist side. So yeah, I’m Mike Weise with the IoT Sandbox in Cleveland, Ohio.
1:03:04
I was formerly with the Boston Blockchain Association in Boston helping
1:03:09
the financial services community understand blockchain technologies and
1:03:14
now I’m focused on IoT. So the leading edge of data subhead future of data and
1:03:23
we’re trying to establish this area and very few people know that this area has a superpower around IoT design
1:03:30
development and manufacturing and so I’m trying to amplify that as a community uh
1:03:37
convenor connector and catalyst. So that’s my introduction.
1:03:42
Yep. Wonderful. Thank you Mike. Great to have you here. And it’s St. Patrick’s Day. So you can
1:03:48
see my Yeah. Yes. My green coat. The green coat. Yes, indeed. Happy St. Patrick’s Day, SA. Yeah. Great. Okay.
1:03:56
So, Mike, first question for you. Um, so there are billions of connected devices sitting inside factories. Um, and Sarah
1:04:03
touched some of those, right? Um, we have logistics networks and critical infrastructure right now. Now, many of
1:04:09
these were never designed with future threats in mind. Where’s the biggest blind spot when it comes to securing
1:04:15
those devices and what’s realistic to fix?
1:04:20
Okay, so yeah, there are billions of connected devices in the manufacturing
1:04:26
setting. Uh I would say uh most of those connected devices are not connected to
1:04:33
each other. So from the supply from the procurement to the production there’s a
1:04:40
lot of systems in factories that are you know potentially gathering data um and
1:04:47
maybe some of them are gathering data but they’re not connected to each other. They’re not integrated with each other.
1:04:53
And so that’s the biggest issue right now is you know people have made
1:04:59
investments in new technologies but they haven’t taken the next step to start you
1:05:04
know connecting them uh to each other so that there’s a unified picture of what’s
1:05:10
going on in the plants on the production line. The other thing that they’re not
1:05:15
doing is on the so so the way I describe it is there’s typically two sides of
1:05:22
IoT. There’s the operational side and there’s the product side. So on the operational side, you have IoT devices
1:05:30
that are gathering data about the production environment, the machines, sensors on machines, etc. On the product
1:05:38
side, you have IoT devices that are deployed with the product, with that
1:05:43
machine that you see rolling down the highway under wraps, you know, on the back of a semitr or smaller devices. uh
1:05:52
like you know lighting systems in Cleveland. There’s a bunch of lighting
1:05:58
systems companies and they put IoT devices on their lighting systems so
1:06:05
that a landscaping company typically can operate these lighting systems remotely
1:06:12
and turn them off, turn them on, etc. have alerts when a light bulb is out,
1:06:17
etc. So, um, the on the on the operational
1:06:24
side, you have all of these systems inside the plant that are working that
1:06:30
aren’t typically connected to each other. And um, so that’s really the
1:06:35
limiting factor right now. And that kind of goes to a more of a human dynamic,
1:06:43
you know, issue rather than a technology issue. The issue is that the the
1:06:51
executives don’t really understand these new technologies and they’re not
1:06:56
investing their time to understand these new technologies. So, you know, IoT,
1:07:04
blockchain, AI, they they’re kind of swimming in this whole sea and they don’t they’re they’re drowning. They
1:07:10
don’t know what to do. And so I know we’re going to get to a question what what should be the next step later, but
1:07:16
I’ll just, you know, signal that they need to sit down with their leadership team and do a boot camp on these new
1:07:24
technologies and how they apply to their their business, what are their, you
1:07:30
know, competitors doing, etc. with trusted subject matter experts on these
1:07:35
new technologies, not vendors. So, um, not that vendors aren’t, you
1:07:42
know, subject matter experts, but a lot of time they’re they’re just focused on their one product.
1:07:48
So, um, so that’s really, you know, what what needs to be done. Can you can you
1:07:54
ask another question? So yeah Mike just before I think you touched on a really important element
1:08:00
that I think the fact that these devices are not interconnected raises major challenges and we know that AI is one of
1:08:06
the solution you need to build centralized AI management right so now we have AI making some of those decisions centrally but that introduces
1:08:13
its own risk um exposure right and so would you like to comment on centralized AI decision making in these environments
1:08:20
and how that amplifies risk um in these kind of environments that should be trusted Sure.
1:08:26
Yeah. Um you you have to uh look at this problem holistically. You have to make
1:08:33
sure that the IoT devices are secure. You have to make sure that the blockchains are generated by the proper
1:08:40
devices. Pretty much you have to make sure everything works together. That’s really
1:08:45
the bottom line. You you cannot just secure one portion of the system uh and
1:08:50
say okay well my sensor’s data is uh uh properly generated it’s got the right
1:08:56
authentication it’s got the right certificate but the person looking at it is the wrong person. So it’s like you
1:09:02
have to solve this holistically. That’s that’s basically bottom line. That’s right. And you have to bring in a
1:09:08
strategy uh you have to develop that holistic strategy as Hamid rightly said
1:09:16
and that’s really hard work that’s where you have to sit the leadership team
1:09:23
crossfunctional leadership team down and say okay first of all what is it and
1:09:31
second of all how do we leverage this and thirdly what are the faith
1:09:37
What should we do right away? What should we do in phase two? So you have
1:09:42
to really account for the who, what, when, where, how, and how much of your
1:09:49
transformation. Sure. Um, absolutely. Thank you. Thank you, Mike.
1:09:55
And thank you to me, Dennis. I think we have one more question from uh from Nick.
1:10:01
Uh, and after that, I think we running out of time. Yeah. So, go ahead. Oh, okay. Ah, okay. Yeah.
1:10:07
Um, okay. Uh, Nicholas. Okay. Question for you, Dennis. Nick had to drop off, so we’re
1:10:12
actually all good. So, okay. No worries. Yeah. Okay. So, Mike, I have another question
1:10:18
for if you don’t mind. Um, okay. So, blockchain is positioned as a solution
1:10:24
for trust and transparency in in complex ecosystems. From your experience
1:10:29
building IoT and blockchain networks, how can it provide pure verified identity for devices and AI agents
1:10:36
without slowing everything down because we can’t compromise performance, right? Not to get your thoughts down.
1:10:45
Okay, you were kind of breaking up there, but I I think I just uh generally understand the
1:10:51
question. First of all, the issue in the industrial heartland and the and in manufacturing is that
1:10:58
very few people are using blockchain right now and they first of all blockchain technologies in general has
1:11:06
not really been ready for prime time and until the last couple years and so uh
1:11:12
but newer generations of blockchain are available. They don’t slow things down.
1:11:19
uh if if nothing else, they can validate the identity of the devices that are on
1:11:26
the network, approved devices or approved AI agents that are on the
1:11:31
network. Um the sources of the data uh
1:11:36
if not the actual data that’s spinning out of the devices and and the agents.
1:11:43
So the other thing that that the blockchain systems can be really good at
1:11:49
is exception only monitoring. So they they can be detecting
1:11:56
the the exceptions in the data and spinning out alerts to humans in the
1:12:03
loop on hey we’ve got a situation with this machine or with this product that’s
1:12:08
coming out of the machine. So I I don’t know if that exactly answers your
1:12:14
question but I think that’s yeah that’s a a good short answer anyway. Yeah absolutely
1:12:21
I know we are running out of time. Let me just add one more thing to that and just just one more just just one more.
1:12:26
Yeah. Um so at SK what we have created this uh created this uh brand new smart
1:12:32
contract engine where you can take events from any source and there are many many sources. For example, time is
1:12:38
a source. Uh, an agent AI is a source and a a hardware IoT device can generate
1:12:44
events that are registered in our blockchain and you can use them as a source. But there’s also actions that
1:12:50
what actions you want to take. Everything comes down to one thing com the company’s policy. The policy has to
1:12:57
be the decision maker, not people. Because people make overreact policies do not overreact. So bringing this a
1:13:04
smart contract that can link events whether they’re agentic or just somebody
1:13:09
presses a button on their mobile phone that’s an event or has to do with for example what action what is the best
1:13:15
action to take right now you can build all of them around one smart contract run it in the background have 10,000
1:13:22
companies running the same same smart contract that is fully tested and we can deliver that at any scale the scale to
1:13:29
us I spent a year making sure that whatever we for one use system as a prototype can be copied by millionfold
1:13:37
because this linearity was as Jake mentioned it’s been the core of what we’ve been trying to do and with that
1:13:43
Dr. Yeah, just to wrap up, obviously thanks to the panelists and for Dennis hosting and for you Hamid coming out
1:13:50
here in person. Um Richard’s comments and others. Really important. And Michael with the Boston Green Cove. I
1:13:56
mean, you can’t get better than that, right? Um I think it’s important to just acknowledge like to our manufacturers
1:14:02
who will be reviewing this that in our in our MIT tech amp program, we’re a ch
1:14:10
training technologist uh with MIT. We’re actually using
1:14:16
devices and inputs to actually simulate the best practices of what we’ll call augmented lean to create technologists
1:14:23
that fill the gap between technicians and engineers. So, we’re bringing a lot of this technology in with sensoring. uh
1:14:32
however having a manufacturer’s strategic evolution plan around security is
1:14:39
essential so that the cyber human connection is understood and that the
1:14:44
IoT uh sort of leakage points right are addressed uh at a global level. So I I
1:14:52
just want to thank you for highlighting what makes sense both in the way we train technologists and the way we hold
1:14:58
space uh for our manufacturers here in the Birkshars and for all those who care deeply about manufacturing uh security
1:15:06
strategic evolution. Um and uh I know you’ll be around for a little bit of lunch and we have another uh experience
1:15:13
and I just want to thank all of the folks at SQE and all of the folks here live for being here and all those who
1:15:18
joined us remotely. So, thank you so much for being uh uh being so engaged with the Bergier Innovation Center hat.
1:15:25
Thank you, Dr. You’re welcome. Thank you.
