The 1s and 0s behind cyber warfare
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0:01 - 0:03This is a lot of ones and zeroes.
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0:03 - 0:06It's what we call binary information.
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0:06 - 0:08This is how computers talk.
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0:08 - 0:10It's how they store information.
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0:10 - 0:11It's how computers think.
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0:11 - 0:13It's how computers do
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0:13 - 0:15everything it is that computers do.
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0:15 - 0:17I'm a cybersecurity researcher,
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0:17 - 0:19which means my job is to sit
down with this information -
0:19 - 0:21and try to make sense of it,
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0:21 - 0:24to try to understand what all
the ones and zeroes mean. -
0:24 - 0:26Unfortunately for me, we're not just talking
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0:26 - 0:28about the ones and zeroes
I have on the screen here. -
0:28 - 0:30We're not just talking about a
few pages of ones and zeroes. -
0:30 - 0:33We're talking about billions and billions
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0:33 - 0:34of ones and zeroes,
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0:34 - 0:37more than anyone could possibly comprehend.
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0:37 - 0:39Now, as exciting as that sounds,
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0:39 - 0:41when I first started doing cyber —
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0:41 - 0:43(Laughter) —
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0:43 - 0:45when I first started doing cyber, I wasn't sure
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0:45 - 0:47that sifting through ones and zeroes
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0:47 - 0:49was what I wanted to do with the rest of my life,
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0:49 - 0:51because in my mind, cyber
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0:51 - 0:55was keeping viruses off of my grandma's computer,
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0:55 - 0:58it was keeping people's Myspace
pages from being hacked, -
0:58 - 1:00and maybe, maybe on my most glorious day,
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1:00 - 1:04it was keeping someone's credit
card information from being stolen. -
1:04 - 1:05Those are important things,
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1:05 - 1:08but that's not how I wanted to spend my life.
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1:08 - 1:10But after 30 minutes of work
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1:10 - 1:11as a defense contractor,
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1:11 - 1:14I soon found out that my idea of cyber
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1:14 - 1:16was a little bit off.
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1:16 - 1:18In fact, in terms of national security,
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1:18 - 1:20keeping viruses off of my grandma's computer
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1:20 - 1:23was surprisingly low on their priority list.
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1:23 - 1:24And the reason for that is cyber
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1:24 - 1:28is so much bigger than any one of those things.
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1:28 - 1:31Cyber is an integral part of all of our lives,
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1:31 - 1:34because computers are an
integral part of all of our lives, -
1:34 - 1:36even if you don't own a computer.
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1:36 - 1:39Computers control everything in your car,
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1:39 - 1:41from your GPS to your airbags.
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1:41 - 1:42They control your phone.
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1:42 - 1:43They're the reason you can call 911
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1:43 - 1:45and get someone on the other line.
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1:45 - 1:48They control our nation's entire infrastructure.
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1:48 - 1:49They're the reason you have electricity,
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1:49 - 1:52heat, clean water, food.
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1:52 - 1:54Computers control our military equipment,
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1:54 - 1:55everything from missile silos to satellites
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1:55 - 1:59to nuclear defense networks.
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1:59 - 2:01All of these things are made possible
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2:01 - 2:03because of computers,
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2:03 - 2:05and therefore because of cyber,
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2:05 - 2:06and when something goes wrong,
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2:06 - 2:09cyber can make all of these things impossible.
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2:09 - 2:11But that's where I step in.
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2:11 - 2:14A big part of my job is defending all of these things,
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2:14 - 2:15keeping them working,
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2:15 - 2:18but once in a while, part of my
job is to break one of these things, -
2:18 - 2:20because cyber isn't just about defense,
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2:20 - 2:22it's also about offense.
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2:22 - 2:24We're entering an age where we talk about
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2:24 - 2:25cyberweapons.
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2:25 - 2:29In fact, so great is the potential for cyber offense
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2:29 - 2:32that cyber is considered a new domain of warfare.
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2:32 - 2:34Warfare.
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2:34 - 2:36It's not necessarily a bad thing.
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2:36 - 2:39On the one hand, it means we have whole new front
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2:39 - 2:40on which we need to defend ourselves,
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2:40 - 2:42but on the other hand,
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2:42 - 2:44it means we have a whole new way to attack,
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2:44 - 2:46a whole new way to stop evil people
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2:46 - 2:48from doing evil things.
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2:48 - 2:50So let's consider an example of this
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2:50 - 2:51that's completely theoretical.
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2:51 - 2:54Suppose a terrorist wants to blow up a building,
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2:54 - 2:56and he wants to do this again and again
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2:56 - 2:57in the future.
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2:57 - 3:00So he doesn't want to be in
that building when it explodes. -
3:00 - 3:01He's going to use a cell phone
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3:01 - 3:04as a remote detonator.
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3:04 - 3:06Now, it used to be the only way we had
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3:06 - 3:07to stop this terrorist
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3:07 - 3:10was with a hail of bullets and a car chase,
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3:10 - 3:12but that's not necessarily true anymore.
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3:12 - 3:14We're entering an age where we can stop him
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3:14 - 3:15with the press of a button
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3:15 - 3:17from 1,000 miles away,
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3:17 - 3:19because whether he knew it or not,
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3:19 - 3:20as soon as he decided to use his cell phone,
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3:20 - 3:23he stepped into the realm of cyber.
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3:23 - 3:27A well-crafted cyber attack
could break into his phone, -
3:27 - 3:29disable the overvoltage protections on his battery,
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3:29 - 3:30drastically overload the circuit,
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3:30 - 3:33cause the battery to overheat, and explode.
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3:33 - 3:35No more phone, no more detonator,
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3:35 - 3:37maybe no more terrorist,
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3:37 - 3:38all with the press of a button
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3:38 - 3:41from a thousand miles away.
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3:41 - 3:43So how does this work?
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3:43 - 3:45It all comes back to those ones and zeroes.
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3:45 - 3:48Binary information makes your phone work,
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3:48 - 3:51and used correctly, it can make your phone explode.
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3:51 - 3:54So when you start to look at
cyber from this perspective, -
3:54 - 3:57spending your life sifting through binary information
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3:57 - 4:00starts to seem kind of exciting.
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4:00 - 4:02But here's the catch: This is hard,
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4:02 - 4:04really, really hard,
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4:04 - 4:06and here's why.
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4:06 - 4:08Think about everything you have on your cell phone.
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4:08 - 4:10You've got the pictures you've taken.
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4:10 - 4:12You've got the music you listen to.
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4:12 - 4:14You've got your contacts list,
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4:14 - 4:15your email, and probably 500 apps
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4:15 - 4:18you've never used in your entire life,
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4:18 - 4:22and behind all of this is the software, the code,
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4:22 - 4:24that controls your phone,
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4:24 - 4:26and somewhere, buried inside of that code,
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4:26 - 4:29is a tiny piece that controls your battery,
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4:29 - 4:31and that's what I'm really after,
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4:31 - 4:35but all of this, just a bunch of ones and zeroes,
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4:35 - 4:36and it's all just mixed together.
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4:36 - 4:40In cyber, we call this finding a
needle in a stack of needles, -
4:40 - 4:42because everything pretty much looks alike.
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4:42 - 4:44I'm looking for one key piece,
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4:44 - 4:47but it just blends in with everything else.
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4:47 - 4:49So let's step back from this theoretical situation
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4:49 - 4:52of making a terrorist's phone explode,
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4:52 - 4:54and look at something that actually happened to me.
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4:54 - 4:56Pretty much no matter what I do,
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4:56 - 4:57my job always starts with sitting down
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4:57 - 5:00with a whole bunch of binary information,
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5:00 - 5:01and I'm always looking for one key piece
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5:01 - 5:03to do something specific.
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5:03 - 5:05In this case, I was looking for a very advanced,
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5:05 - 5:07very high-tech piece of code
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5:07 - 5:08that I knew I could hack,
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5:08 - 5:10but it was somewhere buried
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5:10 - 5:12inside of a billion ones and zeroes.
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5:12 - 5:13Unfortunately for me, I didn't know
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5:13 - 5:15quite what I was looking for.
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5:15 - 5:16I didn't know quite what it would look like,
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5:16 - 5:19which makes finding it really, really hard.
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5:19 - 5:21When I have to do that, what I have to do
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5:21 - 5:24is basically look at various pieces
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5:24 - 5:25of this binary information,
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5:25 - 5:28try to decipher each piece, and see if it might be
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5:28 - 5:29what I'm after.
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5:29 - 5:30So after a while, I thought I had found the piece
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5:30 - 5:32I was looking for.
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5:32 - 5:34I thought maybe this was it.
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5:34 - 5:36It seemed to be about right, but I couldn't quite tell.
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5:36 - 5:39I couldn't tell what those
ones and zeroes represented. -
5:39 - 5:42So I spent some time trying to put this together,
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5:42 - 5:44but wasn't having a whole lot of luck,
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5:44 - 5:45and finally I decided,
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5:45 - 5:47I'm going to get through this,
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5:47 - 5:48I'm going to come in on a weekend,
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5:48 - 5:49and I'm not going to leave
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5:49 - 5:51until I figure out what this represents.
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5:51 - 5:53So that's what I did. I came
in on a Saturday morning, -
5:53 - 5:57and about 10 hours in, I sort of
had all the pieces to the puzzle. -
5:57 - 5:58I just didn't know how they fit together.
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5:58 - 6:01I didn't know what these ones and zeroes meant.
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6:01 - 6:03At the 15-hour mark,
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6:03 - 6:06I started to get a better picture of what was there,
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6:06 - 6:08but I had a creeping suspicion
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6:08 - 6:09that what I was looking at
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6:09 - 6:12was not at all related to what I was looking for.
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6:12 - 6:15By 20 hours, the pieces started to come together
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6:15 - 6:18very slowly — (Laughter) —
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6:18 - 6:20and I was pretty sure I was going down
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6:20 - 6:22the wrong path at this point,
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6:22 - 6:24but I wasn't going to give up.
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6:24 - 6:27After 30 hours in the lab,
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6:27 - 6:29I figured out exactly what I was looking at,
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6:29 - 6:32and I was right, it wasn't what I was looking for.
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6:32 - 6:33I spent 30 hours piecing together
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6:33 - 6:36the ones and zeroes that
formed a picture of a kitten. -
6:36 - 6:38(Laughter)
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6:38 - 6:42I wasted 30 hours of my life searching for this kitten
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6:42 - 6:44that had nothing at all to do
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6:44 - 6:46with what I was trying to accomplish.
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6:46 - 6:49So I was frustrated, I was exhausted.
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6:49 - 6:53After 30 hours in the lab, I probably smelled horrible.
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6:53 - 6:55But instead of just going home
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6:55 - 6:57and calling it quits, I took a step back
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6:57 - 7:00and asked myself, what went wrong here?
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7:00 - 7:02How could I make such a stupid mistake?
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7:02 - 7:04I'm really pretty good at this.
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7:04 - 7:05I do this for a living.
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7:05 - 7:07So what happened?
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7:07 - 7:10Well I thought, when you're
looking at information at this level, -
7:10 - 7:13it's so easy to lose track of what you're doing.
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7:13 - 7:14It's easy to not see the forest through the trees.
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7:14 - 7:17It's easy to go down the wrong rabbit hole
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7:17 - 7:18and waste a tremendous amount of time
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7:18 - 7:20doing the wrong thing.
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7:20 - 7:22But I had this epiphany.
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7:22 - 7:25We were looking at the data completely incorrectly
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7:25 - 7:26since day one.
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7:26 - 7:28This is how computers think, ones and zeroes.
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7:28 - 7:30It's not how people think,
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7:30 - 7:32but we've been trying to adapt our minds
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7:32 - 7:33to think more like computers
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7:33 - 7:36so that we can understand this information.
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7:36 - 7:38Instead of trying to make our minds fit the problem,
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7:38 - 7:40we should have been making the problem
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7:40 - 7:41fit our minds,
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7:41 - 7:43because our brains have a tremendous potential
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7:43 - 7:46for analyzing huge amounts of information,
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7:46 - 7:47just not like this.
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7:47 - 7:48So what if we could unlock that potential
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7:48 - 7:50just by translating this
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7:50 - 7:53to the right kind of information?
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7:53 - 7:54So with these ideas in mind,
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7:54 - 7:56I sprinted out of my basement lab at work
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7:56 - 7:57to my basement lab at home,
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7:57 - 7:59which looked pretty much the same.
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7:59 - 8:01The main difference is, at work,
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8:01 - 8:02I'm surrounded by cyber materials,
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8:02 - 8:05and cyber seemed to be the
problem in this situation. -
8:05 - 8:08At home, I'm surrounded by
everything else I've ever learned. -
8:08 - 8:10So I poured through every book I could find,
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8:10 - 8:12every idea I'd ever encountered,
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8:12 - 8:14to see how could we translate a problem
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8:14 - 8:17from one domain to something completely different?
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8:17 - 8:18The biggest question was,
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8:18 - 8:20what do we want to translate it to?
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8:20 - 8:22What do our brains do perfectly naturally
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8:22 - 8:24that we could exploit?
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8:24 - 8:26My answer was vision.
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8:26 - 8:30We have a tremendous capability
to analyze visual information. -
8:30 - 8:32We can combine color gradients, depth cues,
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8:32 - 8:34all sorts of these different signals
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8:34 - 8:36into one coherent picture of the world around us.
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8:36 - 8:38That's incredible.
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8:38 - 8:39So if we could find a way to translate
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8:39 - 8:41these binary patterns to visual signals,
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8:41 - 8:43we could really unlock the power of our brains
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8:43 - 8:46to process this stuff.
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8:46 - 8:48So I started looking at the binary information,
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8:48 - 8:49and I asked myself, what do I do
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8:49 - 8:51when I first encounter something like this?
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8:51 - 8:52And the very first thing I want to do,
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8:52 - 8:54the very first question I want to answer,
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8:54 - 8:55is what is this?
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8:55 - 8:57I don't care what it does, how it works.
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8:57 - 9:00All I want to know is, what is this?
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9:00 - 9:02And the way I can figure that out
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9:02 - 9:03is by looking at chunks,
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9:03 - 9:06sequential chunks of binary information,
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9:06 - 9:09and I look at the relationships
between those chunks. -
9:09 - 9:10When I gather up enough of these sequences,
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9:10 - 9:12I begin to get an idea of exactly
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9:12 - 9:15what this information must be.
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9:15 - 9:16So let's go back to that
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9:16 - 9:18blow up the terrorist's phone situation.
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9:18 - 9:21This is what English text looks like
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9:21 - 9:22at a binary level.
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9:22 - 9:24This is what your contacts list would look like
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9:24 - 9:26if I were examining it.
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9:26 - 9:28It's really hard to analyze this at this level,
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9:28 - 9:30but if we take those same binary chunks
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9:30 - 9:31that I would be trying to find,
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9:31 - 9:33and instead translate that
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9:33 - 9:35to a visual representation,
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9:35 - 9:37translate those relationships,
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9:37 - 9:38this is what we get.
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9:38 - 9:40This is what English text looks like
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9:40 - 9:43from a visual abstraction perspective.
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9:43 - 9:44All of a sudden,
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9:44 - 9:45it shows us all the same information
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9:45 - 9:47that was in the ones and zeroes,
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9:47 - 9:49but show us it in an entirely different way,
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9:49 - 9:51a way that we can immediately comprehend.
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9:51 - 9:54We can instantly see all of the patterns here.
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9:54 - 9:56It takes me seconds to pick out patterns here,
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9:56 - 9:59but hours, days, to pick them out
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9:59 - 10:00in ones and zeroes.
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10:00 - 10:02It takes minutes for anybody to learn
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10:02 - 10:03what these patterns represent here,
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10:03 - 10:05but years of experience in cyber
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10:05 - 10:07to learn what those same patterns represent
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10:07 - 10:09in ones and zeroes.
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10:09 - 10:10So this piece is caused by
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10:10 - 10:12lower case letters followed by lower case letters
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10:12 - 10:14inside of that contact list.
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10:14 - 10:16This is upper case by upper case,
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10:16 - 10:18upper case by lower case, lower case by upper case.
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10:18 - 10:21This is caused by spaces. This
is caused by carriage returns. -
10:21 - 10:22We can go through every little detail
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10:22 - 10:25of the binary information in seconds,
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10:25 - 10:29as opposed to weeks, months, at this level.
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10:29 - 10:30This is what an image looks like
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10:30 - 10:32from your cell phone.
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10:32 - 10:33But this is what it looks like
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10:33 - 10:35in a visual abstraction.
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10:35 - 10:37This is what your music looks like,
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10:37 - 10:39but here's its visual abstraction.
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10:39 - 10:41Most importantly for me,
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10:41 - 10:44this is what the code on your cell phone looks like.
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10:44 - 10:47This is what I'm after in the end,
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10:47 - 10:49but this is its visual abstraction.
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10:49 - 10:51If I can find this, I can't make the phone explode.
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10:51 - 10:54I could spend weeks trying to find this
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10:54 - 10:55in ones and zeroes,
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10:55 - 10:57but it takes me seconds to pick out
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10:57 - 11:00a visual abstraction like this.
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11:00 - 11:03One of those most remarkable parts about all of this
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11:03 - 11:05is it gives us an entirely new way to understand
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11:05 - 11:09new information, stuff that we haven't seen before.
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11:09 - 11:11So I know what English looks like at a binary level,
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11:11 - 11:13and I know what its visual abstraction looks like,
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11:13 - 11:17but I've never seen Russian binary in my entire life.
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11:17 - 11:18It would take me weeks just to figure out
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11:18 - 11:21what I was looking at from raw ones and zeroes,
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11:21 - 11:23but because our brains can instantly pick up
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11:23 - 11:26and recognize these subtle patterns inside
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11:26 - 11:27of these visual abstractions,
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11:27 - 11:29we can unconsciously apply those
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11:29 - 11:31in new situations.
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11:31 - 11:32So this is what Russian looks like
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11:32 - 11:34in a visual abstraction.
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11:34 - 11:36Because I know what one language looks like,
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11:36 - 11:37I can recognize other languages
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11:37 - 11:39even when I'm not familiar with them.
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11:39 - 11:41This is what a photograph looks like,
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11:41 - 11:43but this is what clip art looks like.
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11:43 - 11:45This is what the code on your phone looks like,
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11:45 - 11:48but this is what the code on
your computer looks like. -
11:48 - 11:50Our brains can pick up on these patterns
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11:50 - 11:52in ways that we never could have
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11:52 - 11:54from looking at raw ones and zeroes.
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11:54 - 11:56But we've really only scratched the surface
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11:56 - 11:58of what we can do with this approach.
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11:58 - 12:00We've only begun to unlock the capabilities
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12:00 - 12:03of our minds to process visual information.
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12:03 - 12:05If we take those same concepts and translate them
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12:05 - 12:07into three dimensions instead,
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12:07 - 12:10we find entirely new ways of
making sense of information. -
12:10 - 12:13In seconds, we can pick out every pattern here.
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12:13 - 12:15we can see the cross associated with code.
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12:15 - 12:16We can see cubes associated with text.
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12:16 - 12:19We can even pick up the tiniest visual artifacts.
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12:19 - 12:21Things that would take us weeks,
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12:21 - 12:23months to find in ones and zeroes,
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12:23 - 12:25are immediately apparent
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12:25 - 12:27in some sort of visual abstraction,
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12:27 - 12:28and as we continue to go through this
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12:28 - 12:30and throw more and more information at it,
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12:30 - 12:33what we find is that we're capable of processing
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12:33 - 12:35billions of ones and zeroes
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12:35 - 12:36in a matter of seconds
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12:36 - 12:40just by using our brain's built-in ability
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12:40 - 12:42to analyze patterns.
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12:42 - 12:44So this is really nice and helpful,
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12:44 - 12:46but all this tells me is what I'm looking at.
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12:46 - 12:48So at this point, based on visual patterns,
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12:48 - 12:50I can find the code on the phone.
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12:50 - 12:53But that's not enough to blow up a battery.
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12:53 - 12:54The next thing I need to find is the code
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12:54 - 12:56that controls the battery, but we're back
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12:56 - 12:58to the needle in a stack of needles problem.
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12:58 - 13:00That code looks pretty much like all the other code
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13:00 - 13:02on that system.
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13:02 - 13:05So I might not be able to find the
code that controls the battery, -
13:05 - 13:07but there's a lot of things
that are very similar to that. -
13:07 - 13:09You have code that controls your screen,
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13:09 - 13:11that controls your buttons,
that controls your microphones, -
13:11 - 13:13so even if I can't find the code for the battery,
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13:13 - 13:15I bet I can find one of those things.
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13:15 - 13:18So the next step in my binary analysis process
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13:18 - 13:19is to look at pieces of information
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13:19 - 13:21that are similar to each other.
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13:21 - 13:25It's really, really hard to do at a binary level,
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13:25 - 13:29but if we translate those similarities
to a visual abstraction instead, -
13:29 - 13:31I don't even have to sift through the raw data.
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13:31 - 13:33All I have to do is wait for the image to light up
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13:33 - 13:36to see when I'm at similar pieces.
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13:36 - 13:39I follow these strands of similarity
like a trail of bread crumbs -
13:39 - 13:42to find exactly what I'm looking for.
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13:42 - 13:43So at this point in the process,
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13:43 - 13:45I've located the code
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13:45 - 13:46responsible for controlling your battery,
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13:46 - 13:49but that's still not enough to blow up a phone.
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13:49 - 13:51The last piece of the puzzle
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13:51 - 13:53is understanding how that code
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13:53 - 13:54controls your battery.
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13:54 - 13:57For this, I need to identify
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13:57 - 13:59very subtle, very detailed relationships
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13:59 - 14:01within that binary information,
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14:01 - 14:02another very hard thing to do
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14:02 - 14:05when looking at ones and zeroes.
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14:05 - 14:06But if we translate that information
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14:06 - 14:08into a physical representation,
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14:08 - 14:11we can sit back and let our
visual cortex do all the hard work. -
14:11 - 14:13It can find all the detailed patterns,
-
14:13 - 14:15all the important pieces, for us.
-
14:15 - 14:18It can find out exactly how the pieces of that code
-
14:18 - 14:21work together to control that battery.
-
14:21 - 14:24All of this can be done in a matter of hours,
-
14:24 - 14:25whereas the same process
-
14:25 - 14:28would have taken months in the past.
-
14:28 - 14:29This is all well and good
-
14:29 - 14:32in a theoretical blow up a terrorist's phone situation.
-
14:32 - 14:35I wanted to find out if this would really work
-
14:35 - 14:37in the work I do every day.
-
14:37 - 14:40So I was playing around with these same concepts
-
14:40 - 14:44with some of the data I've looked at in the past,
-
14:44 - 14:46and yet again, I was trying to find
-
14:46 - 14:48a very detailed, specific piece of code
-
14:48 - 14:52inside of a massive piece of binary information.
-
14:52 - 14:54So I looked at it at this level,
-
14:54 - 14:56thinking I was looking at the right thing,
-
14:56 - 14:58only to see this doesn't have
-
14:58 - 15:00the connectivity I would have expected
-
15:00 - 15:01for the code I was looking for.
-
15:01 - 15:04In fact, I'm not really sure what this is,
-
15:04 - 15:05but when I stepped back a level
-
15:05 - 15:07and looked at the similarities within the code
-
15:07 - 15:09I saw, this doesn't have similarities
-
15:09 - 15:11like any code that exists out there.
-
15:11 - 15:13I can't even be looking at code.
-
15:13 - 15:15In fact, from this perspective,
-
15:15 - 15:17I could tell, this isn't code.
-
15:17 - 15:19This is an image of some sort.
-
15:19 - 15:21And from here, I can see,
-
15:21 - 15:24it's not just an image, this is a photograph.
-
15:24 - 15:25Now that I know it's a photograph,
-
15:25 - 15:28I've got dozens of other
binary translation techniques -
15:28 - 15:31to visualize and understand that information,
-
15:31 - 15:33so in a matter of seconds,
we can take this information, -
15:33 - 15:36shove it through a dozen other
visual translation techniques -
15:36 - 15:39in order to find out exactly what we were looking at.
-
15:39 - 15:41I saw — (Laughter) —
-
15:41 - 15:44it was that darn kitten again.
-
15:44 - 15:46All this is enabled
-
15:46 - 15:47because we were able to find a way
-
15:47 - 15:49to translate a very hard problem
-
15:49 - 15:52to something our brains do very naturally.
-
15:52 - 15:54So what does this mean?
-
15:54 - 15:55Well, for kittens, it means
-
15:55 - 15:58no more hiding in ones and zeroes.
-
15:58 - 16:01For me, it means no more wasted weekends.
-
16:01 - 16:04For cyber, it means we have a radical new way
-
16:04 - 16:07to tackle the most impossible problems.
-
16:07 - 16:08It means we have a new weapon
-
16:08 - 16:11in the evolving theater of cyber warfare,
-
16:11 - 16:12but for all of us,
-
16:12 - 16:14it means that cyber engineers
-
16:14 - 16:16now have the ability to become first responders
-
16:16 - 16:18in emergency situations.
-
16:18 - 16:20When seconds count,
-
16:20 - 16:23we've unlocked the means to stop the bad guys.
-
16:23 - 16:25Thank you.
-
16:25 - 16:28(Applause)
- Title:
- The 1s and 0s behind cyber warfare
- Speaker:
- Chris Domas
- Description:
-
Chris Domas is a cybersecurity researcher, operating on what’s become a new front of war, "cyber." In this engaging talk, he shows how researchers use pattern recognition and reverse engineering (and pull a few all-nighters) to understand a chunk of binary code whose purpose and contents they don't know.
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDTalks
- Duration:
- 16:45
Olivia Cucinotta edited English subtitles for The 1s and 0s behind cyber warfare | ||
Olivia Cucinotta edited English subtitles for The 1s and 0s behind cyber warfare | ||
Olivia Cucinotta edited English subtitles for The 1s and 0s behind cyber warfare | ||
Olivia Cucinotta edited English subtitles for The 1s and 0s behind cyber warfare | ||
Peter Petrov commented on English subtitles for The 1s and 0s behind cyber warfare | ||
Peter Petrov commented on English subtitles for The 1s and 0s behind cyber warfare | ||
Morton Bast edited English subtitles for The 1s and 0s behind cyber warfare | ||
Morton Bast edited English subtitles for The 1s and 0s behind cyber warfare |
Peter Petrov
To me there is a mistake in the original at 10:49 - 10:51
The text reads "If I can find this, I can't make the phone explode." but there is no sence in this sentence. Following the talk it should be "If I can't find this, I can't make the phone explode."
Peter Petrov
I mean sense above.