[ticking clock begins]
[chess pieces moving]
[ticking clock continues]
Our next speaker
will actually be speaking
again about game theory and homeland security enterprise,
and that's Dr. Jun ...
Okay, I'm gonna say Dr. J.
because I'm messing up the name really bad.
He'll come out and speak to you a little bit about
some of his work, some of the things that
are interests, hopefully you'll find those of interest as well.
And what I ask is
the interaction, the dialogue with the
first speaker was really good,
do that. Ask the questions. You should get a benefit out of this.
Even during the presentation, say I got a question,
ask the questions, because I want you to walk away thinking
I learned something different.
Or at least I opened up,
mentally, I'm thinking of a concept I would never
have considered before.
And the beauty of this is
when you get back to your
assigned area, stations, regional commands, things of that nature
you can get back on our website,
the stuff's recored,
the agendas are on there,
the PowerPoints are on there,
the different sections,
but more importantly, it's gonna have all their contact information.
So down the road ... [inaudible]
... question for Dr. [inaudible]
You'd sent a, and all three of them have actually
have encouraged,
because their interaction with you
is also really valuable,
and quite honestly, I think it's more valuable for them than it is
for you to them,
because they're listening to some of the perspectives,
and again they want their research to actually
have a practical value.
So, sir, here you go.
And you should be all set up.
Hi good morning.
[Audience] Good morning.
Thank you, my name is
Jun Zhuang, some people call me "June,"
some people call me "Jung," some people call me
"June."
The authentic way to do that is [inaudible],
but I recognize that either way that they call me.
And so
today I'm going to talk a little bit about game theory
and homeland security research that I've been doing
the past,
like maybe ten or twelve years.
And I did not list all my collaborators here,
as there are many, many of my collaborators here,
but I did list my sponsors here,
because I've been sponsored by National Science Foundation, DHS,
Air Force, Department of Energy, and
also through
the CREATE center and the STAR center that Victor just mentioned.
And
So overall, research [inaudible]
have been working on game theory for many,
many years, and published a couple of papers
and so I put all the journal,
the article titles, into this word cloud,
and we find that game is really the key word.
And, of course, there's also talk about terrorism,
the defense, and
Homeland Security, resource allocation, mathematical modeling,
and if you are interested in reading academic papers,
they are all downloadable from my
webpage. From this page.
And
so let's talk about a lot of
a lot of games, but if we're gonna talk about games,
we need to talk about who are the players?
And for this,
and these games are dealing with disasters and
Homeland Security,
so if I talk about the disasters we, basically,
classify disasters into two types.
One is a adaptive disasters.
Such is terrorism or cyber threats,
on the right side.
Or the other one is like natural disasters,
like earthquakes, or tornados, or snowstorms
when people coming from Buffalo,
and then they are not adaptive threats.
And the difference between this is a,
suppose like we
viewed New Orleans like a dam, very, very strong,
like hurricane Katrina would still hit the earth [inaudible]
[inaudible]
our puzzle here.
And then,
but if we like
lived different like New York city, very, very  [inaudible]
then the terrorists maybe switch target very easily
to Boston or Chicago.
So in that sense like the
terrorists could be very strategic, could be very adaptive
and how to
take that into consideration when we
allocate limited resources? That's a key
key idea of this game theory
applications for the Homeland Security.
And when we talk about players, players in this
in this context we,
first off we will have lots of
people from the government sectors.
I believe that's many, if not most of the
colleagues here, you're from government sectors in this room.
And for government we have federal government,
we have local government, we have state government,
and of course sometimes we're also dealing with the
foreign governments, especially
dealing with a lot of like treaties and
other intergovernmental collaborations.
And then we have the private sectors.
We have the private corporations,
[inaudible],
like you and me.
We also, like different players they have different payoffs
they have different strategies, they have different
objectives.
And the question is how to
get along with each other and how to aline your
interests together
in this Homeland Security and the disaster
management context.
And, so like, different governments have different
options they can do. They can send the patrols, they can
like invest in some counter measures, and they can
send the [inaudible].
Or, they can put like more sensors.
So, as they have grants,
then they collect taxes, and then
they also like provide like foreign aides, foreign subsidies,
like between governments.
And all those,
like the resource allocation, they have some purpose.
Maybe they need
some other parties to give back, or pay back somehow.
And then from the
private corporations, private sectors perspective
it is the same. They also have their own missions,
most of them they are for profits,
but they also have like the social responsibilities,
and then they can
pay the tax, but they also need to do their
private investment by themselves. Like actually
read a report
like from DHS, like 80% of the
national critical infrastructures are owned by private sectors.
They are not owned by
federal governments.
Now how to
how to protect like 80% of the critical infrastructures
very well considering that
they're actually owned by private sectors.
And so that's actually a pretty interesting
and important, critical public/private
partnerships problems, and how to
make a win-win situation, rather than
rather than like a
a tense, and tensions between
between each other.
So that's how game theory could provide a framework
so that we can
think about that, how to, first of all for
how to deal with adaptive adversaries.
And second of all, how to
[inaudible] a win-win
public/private partnerships between the
different sectors from the defenders'
side.
And of course, when we talk about different actions there
in general we can classify actions into the pre
event action, like the pre-event
prevention, the preparation,
and also we can talk about the post-event
like we leave and the investigation.
And sometimes
it's very tricky to do this balance, and
I think
I think that in most cases
the post-events release is
got lots of, like media
like attractions. Budgets is relatively easy to spend,
to justify,
but actually it's very
not that cost-effectiveness.
So there's some research that suggests that every
every one dollar spent, like
before the event happens, it's actually worth
like four dollars, or maybe ten dollars of the event that happens.
So, however,
if you, before the event happens
you do not know where the
terrorist would attack and where
like the illegal immigrants would enter,
and you don't know the location, you don't know the magnitude
and how could you allocate resource with this uncertainty?
So that's a key challenge.
But [inaudible]
to do some mathematical modeling
to use some of the data
and try to do some quantitative analysis that would be,
provide some
helpful decision-support tools
for this types of problems.
And what is game theory?
The first speaker already talked about game theory
and
so basically this is a branch of applied mathematics,
and I don't know how many of you like mathematics in this room?
How many of you hate mathematics?
Alright you don't have to raise your hand [chuckles]
[inaudible]
But mathematics is not that,
it could be fun. It could be,
but it could be boring also.
But game theory is basically a branch of applied mathematics,
It considers
how to mathematically
capture the behavior in the strategic situation.
And especially, individual success not only depends on what
they do, but also depends on what other people do.
In order for
me, the decision-maker to be successful,
it not only depends on what I do,
but it also depends on what other people do.
So that's a key
concept in the game theory,
especially in the Homeland Security
area that's,
it's whether you're going to be successful or not,
not only depends on what you do, but also it depends on
how the adversaries and how the other
partners
respond
to what you do.
So that's,
we want to keep that into consideration
when we make any of the important decisions.
Game theory has been applied to many, many different areas
like in biology and the population evolution
people talk about using game theory to study how
some certain populations and
species evolve, and that's why some certain
species like
dies.
And in the transportation.
And I just had a nice conversation with one of the colleagues.
In this area they're
either gonna be [inaudible] or gonna be nothing.
But then, transportation why the congestion could happen?
The congestion is always the same,
but the congestion happens only if there's much more
transport travelers
choose the same route at the same time,
and then the congestion happens.
So game theory actually has been used to study the
the traveler's equilibrium. Talk about the,
if we have multiple way of choices,
then how to optimally
like choose
choose a route so that you are
you are better off not to
be caught into the congesting traffic,
and actually technology could provide one of the
tools like the
real
real time GPS
could
provide a support, like Google Maps could provide a support,
so that every time you look at a map
see where's it's red, where it's green
so that you can
try to avoid.
But you know what, if every people
tried to reroute, maybe
the ways that you're rerouting could become congested.
So it becomes equilibrium
so how to do equilibrium solution
so that
every people kind of balance out.
And then computer networks.
Lots of people, actually
most people are using computers nowadays,
but a computer network itself
is a games
not only between
the games between the hackers and yourself,
but also between you and the
your colleagues.
Fo example, like at the universities
universities provide free downloadable anti-virus software.
But why is that?
Is that really because the university really cares about
the individual computers?
Maybe, maybe not.
But actually,
if you do not [inaudible],
if the university does not provide this for free,
nobody will want to spend like five more dollars
to purchase that,
and if nobody
spend five dollars,
not to mention it's actually fifty dollars or like
one hundred dollars,
but if people are not willing to
pay like five dollars, twenty dollars on anti-virus software
then your computer itself could turn
into a [inaudible] sending this virus
to many other people on the same network.
So it becomes a
it becomes games between the defenders
facing the hackers'
threats. Like cyber security actually becomes a very,
more and more,
important threat in this
in this area.
And,
but hackers are also very adaptive.
The hacking cost is almost zero,
and they can,
they can vary.
They can also choose different targets if you're already
very different, they're like a
target.
Where, I mean the target
corporation there,
then you can, maybe they can
easily switched to other targets.
And then,
and then how to take that into consideration when we
do the problems. And then last year I did a
project with DHS, talk about the
Cyber Security Information Sharing Project.
Let's suppose you
have like vulnerabilities for an organization,
do you want to share this information
to the
to the government?
Do you want to share this information to your
you peer corporations?
And why?
There's pros and cons of doing these ads,
and for the government's perspective how to
regulate. How to
provide subsidies so that
people are
like could be safely and
burden-free to share information with each other.
Now political science, we saw the elections
and lots of games going on
like in the past one month.
We don't want to say too much about that [chuckles] anymore.
Now health care itself is also a game, right?
Health care systems, there are lost of players here,
let's talk about that here.
Talk about
like the insurance companies, the hospitals
the nurses, the medical doctors,
the pharmaceutical companies, the patients,
they're all the different groups.
And then,
basically if you want to save some of the cost,
basically you're cutting other people's jobs and then
so what is a trade off?
And how do we create a win-win situation in this whole
system. Like game theory has already been
applied like gradually into that area as well.
Like business and supply chain, there are lots of
supply chain players like the,
including the producers, the manufacturers,
the shippers,
and also the retailers and the consumers.
Game theory has been studying there too.
The real reason why
why I study game theory a lot and why
academic life is because I really enjoy the
personal thinkings of game theory. I just
I just cannot stop thinking that way so I have a
one wife, I have three kids, then I have department chair,
then I have my
six Ph.D. students and many other
like mass of students ...
[inaudible]
... how to
think like from a game's perspective that what I do,
not only how I win,
not only depends on what I do,
but it also depends on what they do,
but in order for them to do what I want them to do
I need to
probably I want to provide some incentives,
probably I want to keep their interest in mind.
And then,
so actually that becomes a
becomes like a personal thinking or philosophy,
that when you
when you make your own decision-makers
try to think about who are the stakeholders?
What's their decision-making process?
And how to put that into a framework
when you make your own decisions.
So that's really
like the game theory
thinkings.
And methodology, I suppose we can
skip that slide for this
for this room. But basically game theory could be applied,
could be merged with network science
so that we can do the games with networks.
And we can, game zero could be
applied with dynamic programming.
So we can do dynamic games,
can be married with
like robust optimization so we can
do robust game theory. We can
study like the behavior games when we
study the behavioral science with the game theory.
So game theory
is really not
like a
stand alone
like branch of science, it's actually
it could be easily
merged, integrated, with many, many other
disciplines so that we can
deal with like more realistic and more
interesting scenarios.
And the key components of the game.
And I believe that in your [inaudible]
post the test
like a
questionnaire so you can
you can check the box there.
And so the key components of the game
first we need to talk about who are the players?
The players are basically the decision-makers.
If there's stakeholders who are impacted by a decision,
but they're not
making any of the
decision,
then they are not players.
They are not players in the game theory context.
However, if they do make some decisions,
including protests, including
other types of, like personal investment,
then they are basically the players.
For each of the players, we need to talk about
what is their options?
What's their alternative? What could they do?
And then, there's also sometimes called moves.
And then we talk about sequence of moves.
Sequence of moves basically
could be who moves first, who moves second,
do they move simultaneously?
Simultaneously basically means they are moving,
it does not have to be moving exactly at the same time.
As long as
when I make my decisions, the other players do not know
what my decision
is when they make their own decisions,
that is considered simultaneous moves.
And then we can talk about what is objectives,
what is the payoffs?
And how the objectives and the payoffs not only
depend on
their own decisions, but also it depends on
what are other people's decisions.
And then what is information structure there?
Do people have complete information?
In game theory we typically
we assume [inaudible] information is the first step.
But then we can,
easily could be
argued that that is not really true.
Adversaries may have incomplete information,
or you may have incomplete information,
but adversary maybe have incomplete information [inaudible].
And then, how to
model incomplete information,
information symmetry,
and send
studies of valuable information,
and studies of valuable intelligence, study
that's worth, what did you do
in order to make the decisions with incomplete information.
[inaudible] What is time?
Is this is a repeated game, or is that a
like a single shot game?
And is there any of the ending point?
Sometimes, one of the mistakes that people could make is
we assume that each game is just a one-time shot.
Actually the
solution, equivalent solution could easily change
if it's a dynamic game.
And we're gonna talk more
very shortly.
Equilibrium.
Equilibrium is a solution concept for game theory.
It's a
basically it talks about, at some point
[inaudible] at some point
that nobody is a
better off by
switching, or deviating from that
strategy, from that solution, without other people deviating.
So that we can
reach a stable point from all the
parts.
And then, inside simple attacker-defender games
is, if you look at the diagram on the left side,
attacker effort could actually,
the x-axis is a defense investment,
so actually it could first increase then decrease
in the defense investment.
So
first of all, if the defense investment is zero,
or it's very, very low
then attacker does not need to spend too much effort
in order to be successful.
But if the defense investment is infinity,
were hypothetically infinity, there's no way the attacker could win.
So the attacker would be deterred in that sense.
But in the between sometimes we,
theoretically we've proved that
attack effort could first increase, then decrease.
And why?
Because if you do spend a little bit of defense,
in order for the attacker to be successful
the attack [inaudible] spend more
in order to
get more advantage in this game
so that
the attack effort could increase.
So that part actually could be
ignored in practice.
This could be counterintuitive.
When you spend some of the defense there?
Why do they fire back?
... Spend more efforts from the adversary side?
And then,
so this is something called best response,
as the first speaker mentioned.
So attack effort as a function,
best response function as a defense effort.
And then if we put attacker's best response and
defender's best response together,
we can get some of the
some point called a Nash equilibrium point.
So this red one is actually one of the
potential attacker best response.
So the blue one is a defender's best response,
if we put them together the circle here would be
the Nash equilibrium point. So at this point
the difference in investment is about 1.3,
and attack effort's investments is 0.1.
So this is about
simultaneous game.
Nash equilibrium in this particular example.
However, we also studied the sequential games.
The difference between sequential games
is
that in the sequential game
the defender move first by
by disclosed was their strategies.
Some of the disclosures is
is voluntary.
Some of these disclosures are mandatory
by the government of regulations.
Some of the disclosures aren't avoidable.
Like if you
put like a fence there, like a wall there,
then there's no way that people cannot observe that.
And then by doing that, you're basically playing a sequential game,
because adversaries see there's a fence,
or there's barrier, or there's walls there
and then they're going to make
best response to that.
And then,
then in that case,
we are going to play a sequential game.
So in that sequential game we can
we can still consider what is attacker's efforts there,
and then we can see that for each
combinations of the attacker
effort and defense investment, what is defender's
utilities, or what is a defender's payoffs?
And then we can
Draw the best response
the indifference curves where the
defender,
which is the lower, the better for the defender,
and then we can
find the intersections between this
indifference curves and the best response curves.
That would be the
equilibrium solutions for the
defense investment, which is a green star.
And we see that a green star is better than this circle
in terms of having higher
defender payoffs,
but this green
star would,
it would
include like higher defense investment,
however the attack effort is deterred.
And then of course you can
spend more money for the defender's side,
but spending more money is not,
may not be justified. You may
spending more money for the defender's side
it may be waste of
money because the attacker's already
been deterred.
So the question is what is optimal level of defense
in order to
deter the attacker?
And then
so one of the insides from the previous page
actually would prove that mathematically
in the games of
complete information
the defender always wants to disclose,
always want to
play the sequential game, the [inaudible] game.
And then
that means that whatever the defense is we want to
we want to disclose that to the public,
and we want to disclose that
to the adversaries.
And then this may not
be always true,
especially in this Homeland Security context.
Sometimes we want to put something
like a secret.
Sometimes we want to put something,
like even we put some deception there,
like decoys.
And then we published a couple of papers,
and basically inside all the papers is
if the games was no private defender information,
in other words,
that attacker,
that adversary knows everything about the defender.
Then there's a
truthful disclosure is always preferred
to secrecy and deception.
As long as the cost of truthful disclosure
is relatively low.
However, in the games of the private
defender information
that means
the adversary is uncertain
about the defender's
valuation, about defender's private information.
The secrecy and deception actually could be strictly
preferred by the defender
at equilibrium in order to mimic
the other types of defender.
Even the cost
of such secrecy and deception
is not that trivial.
And some examples, and
so some people, at 5 PM when they get off of work,
and they look at his car,
this car looks like a crappy car
... How many of you would like to
drive this car?
I think I drove this car when I first came to the U.S.
when I was a graduate student
[audience laughter]
I think I paid like 800 dollars for this car.
But actually, this is not a
crappy car, it is actually a brand new car.
It's just the way the crapper car covers ...
[inaudible]
... probably is only 20 dollars that they can
get from some of the markets.
But why does this happen?
This is deception, and deception happens
because the car [inaudible]
maybe have some incomplete information about the valuation
of this defender, of this
car owners, right?
As long as we have some of the
incomplete information,
we may not choose to
like attack this car.
And he maybe attacks the other car, the neighbor car,
which actually created some of the
problems like games between the defenders,
which we are going to talk about
in the next
later.
But as long as the attacker, the adversary has
incomplete information about
some valuations about the defender,
the defender has some,
maybe want to choose,
spend more dollars,
spend some of the non-zero costs like 20 dollars or 100 dollars,
to get this cover in order to
mimic the other types of the defender, which has low
valuation,
in order to deter the adversaries.
And we've probably seen this is in many, many areas.
And like
security notice,
'This area is under 24 hour live
recorded video surveillance.'
How many of you see this sign?
Probably some of you see this sign everyday.
But I got this sign for like 3 dollars on eBay,
and I can probably also print that for free
through my
color printer from my office.
This is just for 3 dollars on eBay,
people can buy this sign
just to put it on your property.
And it probably can
be as effective as
the true, the real
video surveillance system which costs like
1,000 dollars or 500 dollars.
But as long as the adversary has incomplete information
about the
the defense, about the valuation, about the
technology, even about the cost of functions,
and then maybe this could be a
cost-effective way to some randomized
defense, or even self deception.
And then like security cameras, I think it's not
not everywhere, but actually when I first
see these security cameras I always think,
How many of them are working?
And how many of them are real?
And I guess  probably most of them are real,
most of them are working, but
as long as
they are there, they actually
they provide some of the deterrence facts.
But even, it's possible that
maybe 20% of them are not working, they are just
fake cameras there, but they could
still be as effective as real cameras.
Like speed checkup readers,
and sometimes we see speed check up by helicopter,
by aircraft.
[inaudible]
But every time that I saw this sign
I slowed down, because I was almost [chuckles]
likely to be speeding.
But how do you know readers [inaudible]
but how do you know that even the readers there
the reader is able to tell which car is which?
But as long as the readers
as long as the people have these signs,
people actually could slow down, people
could
be better off for everyone for the society.
And this could be
kind of a deception.
And, that honey pot,
honey pot project, we also have a
we did a subproject for the cyber security project
with DHS on the honey pot.
So honey pot project is basically the idea to try to
create [inaudible]
and try to attract the bad guy
so that the bad guy, the hacker tries to hack the
[inaudible] target, and then you can catch him.
This is a deception, but it works, and it works
like the fishing
from, I think there's some fishing operations from some of the
law enforcement
agencies, they also could work.
But as long as the
the bad guys, the adversaries has incomplete information about
yourself.
But remember, the bad guys, attackers
could also be adaptive.
They could also learn.
They are not just,
like ignore,
all this
information.
So we
studied the scenarios where the attackers
they have incomplete information about
the system of vulnerability,
whether the defense system is really
vulnerable or not vulnerable.
The attacker's may not know that.
So lots of literature studies
that attacker's just easier to attack or not attack.
But then in reality
the attacker could spend some effort to learn the system.
To learn the system before they
choose whether to attack or not attack.
And then
by learning they're gonna get a signal,
the signal says, 'Oh the system is vulnerable.'
But the system could be vulnerable,
given the system is vulnerable, the system could also be
invulnerable given the
signal it's still vulnerable.
So there's like a force
[inaudible] ... like two types of ...
interpreting the signals there.
And then so we study the cost of the
learnings of the attackers and how the defenders could
model, could consider the
learning process of the attacker into
the defense
resource allocation process.
And it's not just like one pure [inaudible].
It could be repeated or,
many, many, many times.
So every time that we talk about,
'Okay, we want to deter the adversaries.'
But deter to where?
When the adversaries are deterred
are they just simply switching targets?
Or are they just, like
deferred to next year?
Are they accumulating recourse so they can
have more,
like bigger attacks?
We don't know, and sometimes we probably we can,
it's very difficult to justify
like the value of deterrence, because deterrence
could simply mean that they're
switching targets.
So I presented this at a TSA a couple of years ago,
the TSA you know that like
before 9/11 attacks that every people can
easy to go through airport security, and it's nothing
like compared to nowadays.
But then they like a
shoe bombs, people have to take off their shoes,
then they have liquid bombs, you cannot bring your liquids,
and then you have like
underwear bombs - I don't know what's going on there
[audience laughter]
The adversaries they're basically, they're adapting, right?
They're adapting lots of their
like strategies and
based on whatever technology.
I don't believe technology can really solve the problem.
I think that
technology could solve like
maybe could solve partially the problem,
but what is the bigger picture?
The adversary could easily
get around the technology, and then
lots of investment on the technology
actually could become worthless,
and it could be just a waste of the resources.
And actually it means we need to
from high level, it doesn't mean that we do not like
technology, we definitely do want to
use technology, but
we want to use technology in smart ways,
in a strategic way.
And, so this project that
[inaudible]
... at University of Maryland
which mentioned earlier about the
how to model the portable pathway for human
smuggling and trafficking
along the U.S./ Mexico borders.
So this sort of project we focus on
how to
model other potential
pathways, not only,
not the port of entries, but also between the port of entries.
And then we study, okay there's lots of
consider lots of terrain formation, what is
how possible is
the pathways are or not?
And then we,
actually we viewed a very
very complex, like the off road transportation networks.
And then we
viewed like
decision-support tools
and then so that
the defenders could
with just a switch select the areas,
and then the
and then we
to see where to put the sensors,
and where to put the patrolling strategies.
And then from the bad guys,
we assume the bad guys would
do the second move best response so that it can
choose the
the optimal ways to get around out of the
the sensors.
And then
considering the potential best response of the adversaries,
how to do the first
stage
department of the
of the investment.
And then
so actually
now we have a new president who may
[inaudible] a war, a great war in the Southern borders
and in the next couple of years,
or maybe from the first months, we don't know that.
And then
actually the war project, the fence project
[inaudible] could be a very interesting
research project from the epidemic side,
but that's also could be a very practical
problems. I think probably a couple of
many of you in this room probably would be
thinking about that project.
And where to view the war and
where to build the fence?
And what type of fence?
Like 10 feet, or 20 feet high?
Concrete?
There are many, many different options,
but then
but then from today's
lecture we want people to think about that.
From the adversaries perspective,
what adversary could do?
Are they able to [inaudible] the fence?
Are they able to [inaudible] the war?
Like suppose they view the
view the fence or view the war, are they able to
easily dig a tunnel and then just go through?
Or how difficult is it?
And then, if it's like 2,000 miles,
long, then what is
best sequence?
You're supposed to have limited budgets, what type of
how to allocate the budgets optimally
so that you can
so that you can
maximize the
the total security?
We know that there's no way
to have 100% security right?
And we know that people can
adversaries like
adaptive adversaries can
always try to
find ways to go through.
But the problem is what
how to minimize the risk and how to maximize
the security, considering that they could be smart,
they could be adaptive.
But from their perspective, from adversaries' perspective
there must be some cost of doing that, right?
There's some cost to dig the tunnels,
there's some cost
there's a cost to view this...
[inaudible]
But then from the defender's perspective,
what is optimal ways to do that?
So we did some analysis
using some of the data, [inaudible] data
about Southwest border apprehensions
in the past 20 years,
and then also the total fence [inaudible].
Actually we found it very interesting, they have like a
very [inaudible].
Probably some people in this room could give a better
explanation than I could do,
but at least from the data we see that the
seems like the fence is working.
The longer the fence, the
smaller number of people that we
we would like to apprehend.
And, maybe then can [inaudible] the other way that...
the good way to
explain this is we
we have lots of deterrence.
So we already deter lots of
illegal immigrants.
And, if we do this regression
analysis, actually we find that
we explain like 92% of all the
all the [inaudible].
And actually it fit pretty well in terms of this
this data.
And then we can do
then people talk about, 'Okay this is maybe related to
the U.S. unemployment rate.'
And potentially because
lots of illegal immigrants come here to
try to get jobs here.
And then, we find that yes actually it's a pretty
[inaudible]
so if the
unemployment rate increased,
the actual apprehensions also decreased.
So that means it has also have some
deterrence facts if the
job situation here is bad, then actually
less people would come to the U.S.
There are actually border fences around the world. We have
like 65 countries
in this world that actually have a different
types of fences, around the world.
So this is not really
a crazy idea, but I think there are going to be
building number six is ours.
But the question is how, and where?
And what is the sequence of doing that?
What is the timing of doing that?
So this actually is me
a couple of months ago, in the Great Wall in China,
I don't know whether the wall would look like this or not.
If we want to do some research project actually I would
see like what is the population density of Mexico, and
why we won't study population density, because
if we want to study the location of the walls and what is
what type of walls to build, you may want to
think about from the
who you're trying to prevent, who you're trying to deter.
And this maybe deter,
maybe it's correlated with density.
It's because everything is about travel costs.
So right now I think like only
half, or maybe less than half of the borders have some type of fence.
But why
why this half? And why
lots of rural areas
there's no fence. Because rural areas
there's also like lots of desert areas
and people may not be able to travel that far,
for more than 5 hours in desert areas.
And then
so then everything comes up, eventually come down with
what is the travel costs?
And what is the response times that we need
from the border patrol agencies here.
And then what is the travel cost from the adversaries
and what is the travel cost
from the border patrols.
And then what is the
population density? How we consider that,
and also terrain formation into
this interesting project. I think that will be
some project that I'm very interested to
collaborate with people in this room.
And I think technically I'm
on the lunch time.
What is the timing here?
It's good, 5 more minutes, 10 more minutes?
Don't worry? Okay.
I know people could be hungry.
So let's do ten minutes, let me finish this.
And then another
considerations that have been doing lots of
game theory applications is
people talk about equity. Talk about equity.
What is fairness?
What is equity in homeland security?
So originally we studied a project with urban areas
security initiatives for the DHS projects.
Originally they talk about each of the states
they are going to receive like 0.75% of the
federal budget, regardless of what threat they are facing.
And then that turns out to be like 40% of the total budget
has already been allocated without any of the
risk-based
allocation,
because we have 50 states.
Then the question is how people are going to spend the money?
For some of the states in New York and California
I think each of the people
receive 5$ per capita investment for that, but for
a state like Wyoming, they receive like 40$ per capita.
And then
there's some national news that some of them
like Wyoming, police officers they
buy like luxury cars, like SUV's
and then you have national debates about that.
And then turns out after 2008, they just cut down to half.
Like rather than 0.75,
it becomes 0.375.
Then the question is why is half?
Then [inaudible] by the examples we see that
we do not [inaudible]
resources that are reserved for equity considerations.
But we see that, what is cost of equity?
Because we know that when we're dealing with
adaptive adversaries
we understand that from a Senator's perspective,
or from the Congress's perspective we have to talk about equities,
but from the adversaries perspective
adversaries may not care about equity. They may,
'Well we already attacked New York City, so we should attack
Buffalo.' No, they do not think that way.
So then what is the cost of equities?
We find that the cost of equities actually is
increases convexly, so actually means increasing
speed.
In terms of the equity coefficient
and then in this particular example
we see that we have ten targets.
If the equity coefficient is one,
then each of the targets gets 10%,
but if the equity coefficient is
less than one,
then they are going to have the risk-based
[inaudible] resource allocations.
Of coarse, sometimes
technology
coefficients, when the technology becomes
more and more advanced
then actually we can equity the cost, actually get the
lower and lower, which is good.
Another
I know that today we are going to talk about game theory,
but we have lots of
debates, we have lots of criticism about game theory
in this area.
People always talking about
what if the adversaries are not playing the game with you?
What if they are not strategic in the game theory
sense? How to respond to that?
So originally, I tried to be defensive.
I said, 'Well if they're rational,
if they really want to achieve their goal,
they should play a game.'
And this worse-case scenario, bla, bla, bla, bla,
but eventually I said, 'Okay no, forget about,'
I acknowledge that the adversaries may not
play a game with you, because they may not use game theory.
Then we see that we are being strategic,
playing a game was probably [inaudible]
and they're not strategic was probably the
one minus 'Q.'
But if they're not playing the game with you,
you have to tell us what
they are going to do
[inaudible], maybe from some intelligence.
And then,
then the question is what is the impact
for the defender's real payoffs?
So then we study case studies here,
so this will have ten targets with different urban areas,
in this particular case we assume that a non-strategic
attackers they just want to
they just want to attack New York City, regardless of what.
They just want New York City
So even New York City is
has been very, very, very well defended,
so still want to attack New York City.
So in that case, if this probably is one
New York city will get 100% of resource allocation,
because the non-strategic attackers they just attack
New York City.
But if it's not one, then we want to like kind of
allocate resources for different targets so that
Chicago will not be
that vulnerable if attacker switched to Chicago.
Then we compare three models.
The bottom model
is circles, is a model
where the defender has complete information,
complete information about
about the attacker which have the lowest expected damage.
And then the triangles is the defenders use of game theory.
If the defender uses game theory,
it may not perform that well
if the
the probability of the attackers
is non-strategic is very, very high.
However,
if you do not use game theory, you're gonna get this
square curve.
If you do not use game theory
then in vast
regions
you will perform very, very poor.
Because,
because as long as there's some percentage
of chance that adversaries may use game theory,
may be adaptive
to your threat.
So what is inside of that?
Okay, suppose some people ask your intelligence
what is the probability that
adversaries they are intelligent.
Maybe 15, 50 percent okay,
if they're 15, 50 percent
than using game theory is much, much more robust.
Because if you do not use game theory, you're
expected damage could be way higher.
So this is one way to justify game theory.
So in the next two minutes,
I'm just gonna share personal experience with me about
[inaudible].
I comes from China originally,
and I joined the University of Buffalo
in 2008 and I,
at that time I was
on a working Visa, H1B working Visa,
and then I come back to China to
to have my vacation.
And then in December
2008, I got stuck there, and then basically
the Visa officer in Shanghai consulate
tell me that they have to check my case,
I said okay, how long?
They said maybe four weeks, maybe six weeks,
but it turns out to be more than 100 days.
And actually I think this gentleman here
got like checked for like three weeks as well.
Three weeks is not that
bad compared to my experience, more than 100 days.
And then
during that time it was a very stressful time for me,
because I have to teach, I have to teach online
so I just use the cameras to
videotape myself so that the TA
can play that in the classroom.
But I think, why me? I'm not a terrorist, I'm not a spy
I'm just a professor doing
Homeland Security research.
And then what is the cost
of checking me? There's a lot of disadvantages
to my students, and to my research, and to the university,
but what is the advantage of checking me?
Okay, what if I am a
spy? What if I am a bad guy, or
the terrorist?
Then, maybe they could
catch me during that screening process.
And then so I eventually got my Visa,
after the 100 days,
and then I wrote a paper during that
during that time. I think, okay maybe,
but they are making some tradeoffs, right?
They are checking me.
There's some costs of checking good guys.
[inaudible] There are congestions,
and the congestions are not good,
congestions are not good for the good guys.
And then
so how to balance the congestions and the security
in the presence of strategic applicants
with private information?
I tell them that I'm not
bad guy, but I could be a bad guy from their perspective.
Then how to make these tradeoffs?
So eventually I got this
[inaudible], which turns out to be good.
So we see this again, again, again through airport screening
debates, the pat downs, advancements in technologies,
and then the
risk-based screening,
I believe this afternoon the speaker is going to talk
some more about this.
And then
so this is good, the TSA has started to think about
the good guys
normal travelers' behaviors
that talk about, think about what is the damage of
like what is the loss
in terms of good guys value of time?
Every day there's so many people that go through
airport security screening,
but every other, people spend like 10 minutes there.
It is a huge
economic damage there.
What is risk-based screening?
And of course it depends on the risks.
And then in this research we talk about
how to balance between screening and security,
considering not only the good guy, but also the bad guy,
and also the approver, the
defender's payoffs.
This not only applies to the
airport screening, but also to Visa, and to the borders, and
the maritime transportations.
And so we stop view N stage models,
very complicated mathematical models, and we also
study the expedited security screenings.
And I think in just one minute,
so I will just go through that.
And we collect some of the data to
study what is people's patience time.
For long people are going to lose their patience?
Are they going to get angry? Are they going to switch
transportation mode?
So actually it's kind of a
[inaudible]
like couple of years ago when the
first eh pat-down screening was introduced,
we have the speaker from Washington D.C.
who refused to fly from Washington D.C. to Buffalo because
the possibility to get patted-down.
So he chose to drive, and I think during that Thanksgiving
time that the national traffic
air traffic actually reduced by 2%.
Because lots of people they just
choose to drive.
But if the think about the car accident rates of driving
actually we probably already killed like 300 people
by that policy.
Anyway, so we also studied
[inaudible] modifications using real data.
We understand sometimes data is
not available, sometimes it is available, [inaudible]
but we try our best to try to
validate the models and develop a
like decision-support tools for the
stakeholders.
So I will be around the floor the rest of today,
and I'm very interested to work with
you guys, and I'm very actively seeking
collaborations, especially try to apply the
academic models into reality,
considering the adversary,
adaptive adversary, congestions,
and like global threats.
[Audience applause]
