Operations Research for Homeland Security and Beyond!

Operations Research for
Homeland Security
and Beyond!
Laura Albert McLay, PhD
Associate Professor
University of Wisconsin-Madison
Industrial and Systems Engineering
laura@engr.wisc.edu
@lauramclay
http://punkrockOR.com
Laura Albert McLay, June 4 2016 ISYE 50th Anniversation Reunion @ UW-Madison

Executive summary
Security research investigates how to use scarce resources for
screening aviation passengers, cargo containers, etc., in low risk,
cost-constrained environments.
Better security is achieved by targeting scarce screening resources
at the “riskiest” passengers and doing less screening on most
passengers.
Research has informed policy at the TSA, technical analysis
underlying TSA Precheck implicitly focuses on risk targeting, which
is why it makes the air system safer, in low risk, cost-constrained
environments.

Aviation security:
Past, present, and future
1938!!

One hijacking
encourages
copycats:
Hijackings are
contagious
Metal detectors and X-
ray machines go in
place

A brief history of passenger screening
• Dawn of time until 1970
• Not much!
• 1970
• Surveillance equipment, air marshals
• Feb 1972
• Armed guards to make people feel safe
• Screened by behavioral profile, metal
detector, and ID check
• Dec. 1972
• Metal detector / magnometer

A brief history of passenger screening
• 1996
• Checked baggage for high-risk
passengers screened for explosives
(run by airlines)
• Passenger-baggage matching rejected
• Motivated by Pan Am Flight 103 (1988)
and TWA Flight 800 (1996)
• Sept. 2001
• Times are a changin’

Security is a moving target
Changes in passenger and baggage screening
• November 2001 – Aviation
Transportation and Security Act
• Created the TSA
• Required all checked baggage to be
screened for explosives, Dec. 2002
deadline
• December 2001
• Remove shoes
• 2002 +
• CAPPS II, Secure Flight, etc. for risk-
based screening

Security is a moving target
Changes in passenger and baggage screening
• August 2006
• No more liquids after liquid
explosives used in a bomb attempt
• 2009 - 2010
• TSA starts using explosive trace
portals
• September 2012
• Less screening for seniors (75+) and
children (<12)
• December 2013
• TSA Precheck for reduced security

Checked baggage security before 2001
• Early discrete optimization research dates back prior to
September 11, 2001
• Checked baggage for high-risk passengers screened for explosives
• Selectee and non-selectee screening
• Goal was how to optimally deploy and use limited baggage
screening devices

Checked baggage security models
Flight segment = flight between takeoff and landing of an aircraft
A flight segment is:
• uncovered if 1+ bags on the flight has not been screened
• covered if all selectee bags on it have been screened
Baggage screening performance measures developed in
conjunction with the Federal Aviation Administration:
• Cover the most flights.
• Cover the most passengers on covered flights.
• Cover flights by fully utilizing the devices.

Checked baggage security models
The Uncovered Flight Segment Problem (UFSP):
Find a subset of flights to screen such that we maximize the total
amount of covered flights subject to a screening capacity.
The Uncovered Passenger Segment Problem (UPSP):
amount of passengers of covered flights subject to a screening
capacity.
The Uncovered Baggage Segment Problem (UBSP):
amount of bags screened subject to a screening capacity.
Policy implications?

Important questions
What if you have to
• Take transferring passengers into account?
• Distribute screening capacity to airports and screening stations?
• Distribute screening capacity to airports and screening stations in
discrete pieces?
• Consider weapons of mass destruction (WMD), not just
conventional attacks?
Discrete optimization can answer all of these questions!

Checked baggage challenges in 2001
State of the art
• Existing explosive detection system devices from two manufacturers
• Old technology for screening passengers
Limitation
• Current technology is slow and not effective
• Not enough space for security and security lines in airports
• Infrastructure needed to screen baggage in-line
Ultimate goal
• Good screening devices
• Fast screening (< 10 minutes)
• Do all this in < 14 months!!

The solution was haphazard & piecemeal
• Explosive trace detection
• Uses mass spectroscopy or ion mobility spectroscopy
• Labor intensive when bag is swabbed

Why are homeland security problems good
ISyE problems?
• Limited resources
• Passenger risk assessments
• Human screeners
• Tradeoffs among criteria (efficiency, security, cost)
• Note: TSA has a goal of <10 minutes waiting for screening
• System and goals are always changing
We will always have security challenges, and ISyE/DSOR tools
will always help us address some of these challenges.
Security often improved through deterrent effect, not
detection.

What about screening passengers?

Risk-Based Passenger Screening
Passenger risk assessments have been used since 1996.
Most passengers are low-risk.
What is known: As risk increases, likelihood of a security threat
outcome increases.
Risk-based security: Captured in the Dynamic Aviation Risk
Management System (DARMS) paradigm.
Risk-based screening vs. Random screening
How do we do it?

Risk-based Screening Framework
Know everyone’s risk before they enter security screening;
allocate security resources to match risk.
Final Assessments:
Was there a successful attack?
Was the system being tested?
How do match limited screening resources to passengers?
Assumptions:
Security resources are limited.
Screening procedures make errors
* False alarms, False clears.

How can passengers be assigned?
Ahead of time:
* Integer programming models1
In real-time:
* Markov Decision Processes2
* Control Theory models3
Based on the Sequential Stochastic Assignment Problem (SSAP)
Security resources allocated to a passenger match the retrospective
security resource allocation.
1 McLay, L.A., Jacobson, S.H., Kobza, J.E., 2006
2 McLay, L.A., Jacobson, S.H., Nikolaev, A.G., 2009
3 Lee, A.J., McLay, L.A., Jacobson, S.H., 2009

Real-time simulation of optimal
policy
Time
Passenger
risk

Risk Profiles of screening classes
Passenger riskLaura Albert McLay, June 4 2016 ISYE 50th Anniversation Reunion @ UW-Madison
Conditional distribution of
passenger risk assessment
values

Screening Procedure Reality
Three possible scenarios:
1. Right Screening
2. Under Screening
3. Over Screening

What if you get it wrong?
Will the system be more vulnerable?
Overestimating risk*: True risk level < estimated risk level
When risk is overestimated, high value security resources get
used on low risk passengers, which may leave fewer high value
security resources available for high risk passengers.
Underestimating risk: True risk level > estimated risk level
When risk is underestimated, high value security resources get
used on high risk passengers, which targets more closely the
high value security resources for high risk passengers
* tendency is to overestimate risk

Key observations
Right Screening is ideal, but challenging to attain for all passengers.
Better security is achieved by targeting scarce screening resources
at the “riskiest” passengers and doing less screening on most
passengers.
TSA Precheck implicitly focuses on reducing screening for some to
target resources at “risky” passengers, which is why it makes the air
system safer, in low risk, cost-constrained environments.

Gaming Strategies
Blocking
Overtaxing / decoys
Timing
Trial and Testing
All can disrupt the system in limited resource environments

Bad intentions
We are trying to prevent attacks
Is the goal to identify non-threat passengers with banned
items or threat passengers with bad intentions (and no
banned items)?
Risk based security focuses on the latter

Final thoughts
• Risk reduction, not risk elimination
• If you cannot find a needle in a haystack, make a smaller haystack
• Target limited resources at a small haystack

Security systems
http://www.tsa.gov/about-tsa/layers-security
How to schedule Federal Air Marshalls
How to randomly staff checkpoints at an airport

In the news: we need DSOR
Queueing and scheduling

In the news!
Live at 4 on WISC-TV, May 31, 2016
http://www.channel3000.com/news/Professor-talks-about-science-to-traveling-airport-lines/39814720

Thank you!
Laura Albert McLay, PhD
Associate Professor
University of Wisconsin-Madison
Industrial and Systems Engineering
laura@engr.wisc.edu
@lauramclay
http://punkrockOR.com
Blog posts:
Aviation security, there and back again
Aviation security: is more really more?

References
Jacobson, S.H., McLay, L.A., Kobza, J.E., Bowman, J.M., 2005, “Modeling and Analyzing Multiple Station
Baggage Screening Security System Performance," Naval Research Logistics, 52(1), 30-45.
Jacobson, S.H., McLay, L.A., Virta, J.L., Kobza, J.E., 2005, “Integer Program Models for the Deployment
of Airport Baggage Screening Security Devices," Optimization and Engineering, 6(3), 339-359.
McLay, L.A., Jacobson, S.H., Kobza, J.E., 2006, “A Multilevel Passenger Screening Problem for Aviation
Security,” Naval Research Logistics, 53(3), 183-197.
McLay, L.A., Jacobson, S.H., Kobza, J.E., 2007, “Integer Programming Models and Analysis for a
Multilevel Passenger Screening Problem, “IIE Transactions, 39(1), 73-81.
Nikolaev, A.G., Jacobson, S.H., McLay, L.A., 2007, “A Sequential Stochastic Security System Design
Problem for Aviation Security,” Transportation Science, 41(2), 182-194.
McLay, L.A., Jacobson, S.H., Kobza, J.E., 2008, “The Tradeoff between Technology and Prescreening
Intelligence in Checked Baggage Screening for Aviation Security,” Journal of Transportation Security,
1(2), 107-126.
McLay, L.A., Jacobson, S.H., Nikolaev, A.G., 2009, “A Sequential Stochastic Passenger Screening Problem
for Aviation Security,” IIE Transactions, 41(6), 575-591 (2009 Outstanding IIE Publication Award).
Lee, A.J., McLay, L.A., Jacobson, S.H., 2009, “Designing Aviation Security Passenger Screening Systems
using Nonlinear Control,” SIAM Journal on Control and Optimization, 48(4), 2085-2105.
McLay, L.A., Lee, A.J., Jacobson, S.H., 2010, “Risk-Based Policies for Aviation Security Checkpoint
Screening,” Transportation Science, 44(3), 333-349.

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Operations Research for Homeland Security and Beyond!