Developing Algorithms and Software Assistants for Security Domains

CREATE Research Archive Research Project Summaries 2012 Developing Algorithms and Software Assistants for Security Domains Milind Tambe University of Southern California, tambe@usc.edu Follow this and additional works at: http://research.create.usc.edu/project_summaries Part of the Risk Analysis Commons Recommended Citation Tambe, Milind, "Developing Algorithms and Software Assistants for Security Domains" (2012). Research Project Summaries. Paper 122. http://research.create.usc.edu/project_summaries/122 This Article is brought to you for free and open access by CREATE Research Archive. It has been accepted for inclusion in Research Project Summaries by an authorized administrator of CREATE Research Archive. For more information, please contact gribben@usc.edu.

National Center for Risk and Economic Analysis of Terrorism Events University of Southern California Los Angeles, California Developing Algorithms and Software Assistants for Security Domains October 2011 to September 2012 Milind Tambe University of Southern California tambe@usc.edu "This research was supported by the United States Department of Homeland Security through the National Center for Risk and Economic Analysis of Terrorism Events (CREATE) under Cooperative Agreement 2007-ST-061-RE0001. However, any opinions, findings, and conclusions or recommendations in this document are those of the authors and do not necessarily reflect views of the United States Department of Homeland Security or the University of Southern California." Cooperative Agreement No. 2010-ST-061-RE0001 Department of Homeland Security December 31, 2012

ABOUT CREATE The National Center for Risk and Economic Analysis of Terrorism Events (CREATE) was the first university-based Center of Excellence (COE) funded by University Programs of the Science and Technology (S&T) Directorate of the Department of Homeland Security (DHS). CREATE started operations in March of 2004. This annual report covers the eighth year of CREATE funding from October 2011 to September 2012, the second year under Cooperative Agreement 2010-ST-061-RE0001 from DHS. While the text of this report focuses on the eighth year, all data tables, publications, lists of participants, students, and presentations and events are cumulative from the inception of CREATE. CREATE s research mission is to develop advanced models and tools for risk assessment, economic assessment, and risk management to counter terrorism. CREATE accomplishes this mission through an integrated program of research, education, and outreach, spanning the disciplines of economics, psychology, political science, industrial and systems engineering and information science. CREATE develops models, analytical tools, methodologies and software, and tests these tools in case analyses, representing critical homeland security investment and policy decisions. Due to the cross-cutting nature of research in risk, economics, and risk management, CREATE serves the need of many client agencies at the DHS, including the Transportation Security Agency, Customs and Border Protection, Immigration and Customs Enforcement, FEMA and the US Coast Guard. In addition, CREATE has developed relationships with clients in the Offices of National Protection and Programs, Intelligence and Analysis, General Council, Health Affairs, and Domestic Nuclear Detection. Using a mix of fundamental and applied research, CREATE faculty and students take both the long-term view of how to reduce terrorism risk through fundamental research and the medium-term view of how to improve the cost-effectiveness of counter-terrorism policies and investments through applied research. Please visit www.create.usc.edu for more information. Page 2 of 15

Developing Algorithms and Software Assistants for Security Domains Milind Tambe, University of Southern California tambe@usc.edu 1. Executive Summary... 3 2. Research Accomplishments... 4 3. Applied Relevance: Real world Deployments... 6 4 Collaborative Projects... 9 5 Research Products... 9 5.1 Publications and Reports... 10 5.2 Presentations... 11 5.3 Software Tools and Products... 13 6 Education and Outreach Products... 13 1. Executive Summary This research has been at the forefront of applying computational game theory techniques for security. It has led to a wide range of actual deployed applications of game theory for security. Our first application, Assistant for Randomized Monitoring Over Routes (ARMOR), successfully deployed game theory in practice at the Los Angeles International Airport (LAX) in 2007, and has been in use since. In particular, ARMOR uses game theory to randomize allocation of police checkpoints and canine units. Our second application, Intelligent Randomization in Scheduling (IRIS), is in use by the US Federal Air Marshal Service since 2009 to deploy air marshals on US air carriers. A third application, Game-theoretic Unpredictable And Randomly Deployed Security (GUARDS), for the US Transportation Security Administration is getting evaluated for a national deployment across over 400 United States airports. A fourth application, Port Resilience Operational / Tactical Enforcement to Combat Terrorism (PROTECT), for the United States Coast Guard, has been demonstrated at the Ports of Boston and New York and is actually headed for nationwide deployment. A final application called TRUSTS (Tactical Randomization for Urban Security in Transit Systems) for checking for fare-evaders on LA area metro trains is currently being evaluated in field trials. We are also collaborating with the US Coast Guard on an application for deploying escort boats to protect ferries, which is currently under evaluation for deployment in late 2012. Many other agencies around the globe are now looking to deploy these techniques. These systems focus on the game-theoretic method of providing efficient randomization of security plans and processes. Casting the problem as a Bayesian Stackelberg game, they obtain randomized strategies for security agents; one of the fundamental advances in all these systems then is to provide the fastest algorithms known-to-date to solve such games. The strength of this research is the marriage of strong theoretical game-theoretic foundations with practical applications, and the virtuous cycle of theory and practice to benefit from each other. These deployments of applications in the real-world has led to significant interest from the media and other potential users/customers, and substantial research. Keywords related to the project: Keyword 1: Game Theory, Bayesian Stackelberg games Keyword 2: Security domains Keyword 3: Software scheduling assistants Page 3 of 15

2. Research Accomplishments At the heart of our applications are the efficient algorithms created to solve the very large games to provide optimal strategies for the defender in the Stackelberg games that are deployed. This challenge of fast Stackelberg game solvers is the primary research challenge we have addressed to this point, but this remains a daunting challenge. Furthermore, the presence of uncertainty and human biases further complicate the problem. These algorithms combine computational techniques from Computer Science with the insights from Operations Research literature, and thus are at the cutting edge of both these fields. The advances reported here were necessary for the deployed application; list of key publications is available in the appendix. Figure 1 US Coast Guard Boat patrol, scheduled by PROTECT, on patrol in the port of Boston. Figure 2 IRIS schedules air marshals on board commercial planes. Algorithms For Efficient Scalable Algorithms Scale-up challenges arise in these games due to at least three different reasons: 1. Growth in the number of defender strategies: There may be a very large number of ways in which the limited defender resources may be allocated to targets. For example, in the IRIS system, with just 100 flights, and 10 air marshals, we have 100, i.e. 1.73 10 13 different ways of allocating air marshals to flights. 2. Growth in the number of attacker strategies: The growth in attacker strategies may arise because the attacker may have multiple different ways of evading defender actions and then attack particular targets. This explosion of attacker strategies is seen to arise in the GUARDS system. Indeed, such growth in attacker strategies is also seen in other applications where the defender s actions involve protecting targets embedded in a network, e.g. protecting important locations in a city that are embedded in the city s road network. In such situations, the attacker can follow many different paths to get to the targets of interest. 3. Growth in the number of attacker types: The security forces may be facing many types of attackers. For example, the LAX police need to protect the airport not only from terrorists but also from local LA gangs and even disgruntled employees. When there is an increase in the number of these attacker types, each attacker type increases the computational complexity by an exponential factor. To address these complexities, we have created a range of different algorithms described in the table below. The first game-theoretic algorithms were designed in 2007, and newer algorithms continue to be designed to address on-going challenges. Further improvements are required, and we anticipate that newer algorithms providing additional speedup techniques will continue to emerge. C 10 Page 4 of 15

Example Scale-up: Defender Scale-up: Attacker Scale-up: Algorithm Solution Type Domain Actions Actions Attacker Types (Year) LAX Low Low Medium Approximate ASAP (2007) LAX Low Low Medium Exact DOBSS (2007) FAMS High Low Low Approximate ORIGAMI (2009) FAMS High Low Low Approximate ERASER-C (2009) FAMS High Low Low Exact ASPEN (2010) Urban RANGER High High Low Approximate Security (2010) Urban RUGGED High High Low Exact Security (2011) LAX Low Low High Exact HBGS (2011) FAMS High Low High Exact HBSA (2011) FAMS High Low High Exact HUNTER (2012) LA Metro High Low High Approximate TRUSTS (2012) Social Network High High Low Approximate LSMI (2012) Table 1 List of Algorithms Addressing Scalability in Real-world Security Domains (Most recent work in green) Algorithms for Robust Algorithms and Handling Human Biases Real-world domains present different sorts of uncertainties: there are uncertainties in the preferences of the attackers (Bayesian Games); in their abilities to compute (bounded rationality) and whether human biases affect their decision making. We have developed algorithms geared to handle such uncertainties of the real-world, and plan to continue to develop even more robust algorithms in the future. Example Domain Addressed Issue Algorithm (Year) LAX Rationality / Robustness in Attacker s Observations COBRA (2009) LAX Attacker Preferences (Bayesian Games) HBGS (2011) FAMS Attacker Preferences (Bayesian Games) HBSA (2011) TSA Activities Attacker Capability (attacker circumvents security measures) GUARDS (2011) FAMS Attacker Preferences (Bayesian Games) HUNTER (2012) FAMS Attacker Preferences (Multiobjective) ORIGAMI-A (2012) USCG Attaker s bounded rationality (Quantal Response) PASAQ (2012) FAMS Attacker s bounded rationality (robust optimization) MATCH (2012) Table 2 List of Algorithms Addressing Robustness Issues in Real-world Security Domains (Most recent work in green) Evaluation with Human Subjects We have also evaluated the performance of our algorithms against human subjects. We developed a Pirates and Treasure game modeling the real-security problem at LAX, and compare different Page 5 of 15

approaches, involving 158 human subjects playing 3160 instances of the games in total. The final conclusion was that a model that incorporates both the ideas of robustness and human behavior achieves statistically significant better rewards and also maintains equivalent or faster solution speeds compared to existing approaches. Figure 3 A Screenshot of the "Pirates and Treasure" Game Modeling the Security Problem at LAX. Evaluation of Computational Emotional Contagion Models We have created agent simulations that include three separate phenomena: spread of knowledge, emotional contagion, and social comparison. We have also examined different models of contagion and their applicability to simulating emotional contagion. Recent work has sought to quantify the qualitative findings of social psychology into useable models, primarily drawing from two bodies of research on similar phenomena. We incorporated social and emotional contagion effects and first applied it to an evacuation simulation domain. Applied to real world data from video obtained from panic situations in Amsterdam and Greece, our results show that our models with emotional contagion were able to replicate real behavior with higher fidelity than the established models. 3. Applied Relevance: Real world Deployments Real-world applications are the result of a unique collaboration where university researchers work directly with a security agency for the purpose of creating a useful product to potentially deploy outcomes of research on a national scale. These collaborations to transition research to large-scale real-world deployments have presented valuable lessons. They have taught us how to bridge the culture gap between academic researchers and real-world operators. This section briefly describes our different applications. 3.1 ARMOR Our first application of security games was ARMOR (Assistant for Randomized Monitoring Over Routes). This application emerged in 2007 after police at the Los Angeles International Airport (LAX) approached us with the question of how to randomize deployment of their limited security resources. For example, they have six inbound roads into LAX, and they wished to set up checkpoints. There are not enough police to set up checkpoints on all roads at all times. So the question is where and when to set up these checkpoints. Similarly, they have eight terminals but not enough explosive-detecting canine units to Page 6 of 15

patrol all terminals at all times of the day (a canine unit is limited by the number of hours a dog can work per day). Given that LAX may be under surveillance by adversaries, the question is where and when to have the canine units patrol the different terminals. The police approached us in April 2007 after we had designed our first set of algorithms. While the algorithms were ready, we needed to spend several months acquiring knowledge, understanding how different police units performed their duties, constraints on their operations in terms of shifts of operations, obtaining detailed data on passenger loads at different times of the day at different terminals and so on. The passenger data, for example, influences how payoffs are determined in our underlying game representation --- our adversaries would want to cause maximum harm to civilians and the higher the passenger load, the higher the payoff to the adversaries. By August of 2007, after multiple iterations, the police started using ARMOR for setting up checkpoints and later for canine patrols. The backbone of ARMOR are algorithms for solving Bayesian Stackelberg games as discussed in the following; they recommend a randomized pattern for setting up checkpoints and canine unit patrols. Police provide inputs like the number of available canine units; ARMOR then provides to the police an hour-by-hour schedule for where to set up canine patrols. ARMOR continues to be in use at LAX since 2007 and has undergone periodic updates to its software. The ARMOR system has received numerous accolades for its use. 3.2 IRIS After ARMOR, we were contacted by the Federal Air Marshals Service (FAMS). Their challenge is to randomize allocations of air marshals to flights to avoid predictability by adversaries conducting surveillance (e.g. these might be part of an insider threat), yet provide adequate protection to more important flights. We are focused in particular on some sectors of international flights. Even within that domain, there are a very large number of flights over a month, and not enough air marshals to cover all the flights. To accomplish the goal of randomized allocation of air marshals to flight, we constructed a system called IRIS (Intelligent Randomization In Scheduling). We delivered the system to the FAMS in Spring 2009. After extensive testing, the FAMS started using this system in October 2009. At its backend, IRIS casts the problem it solves as a Stackelberg game and in particular as a security game. We have focused in particular on the special nature of the security game framework to build fast algorithms for IRIS. 3.3 GUARDS After IRIS, our next focus was GUARDS. GUARDS (Game-theoretic Unpredictable and Randomly Deployed Security) was developed in collaboration with the United States Transportation Security Administration (TSA) to assist in resource allocation tasks for airport protection at over four hundred United States airports. In contrast with ARMOR and IRIS, which focus on one installation/applications and one security activity (e.g. canine patrol or checkpoints) per application, GUARDS reasons with multiple security activities, diverse potential threats and also hundreds of end users. The goal for GUARDS is to allocate TSA personnel to security activities conducted to protect the airport infrastructure; GUARDS does not focus on checking passengers. Page 7 of 15

GUARDS again utilizes a Stackelberg game, but generalizes beyond security games and develops a novel solution algorithm for these games. GUARDS has been delivered to the TSA and is currently under evaluation and testing for scheduling practices at an undisclosed airport. If successful, the TSA intends to incorporate the system into their unpredictable scheduling practices nationwide. 3.4 PROTECT Beyond ARMOR, IRIS and GUARDS, more recently, we have developed a game-theoretic system that is deployed by the United States Coast Guard (USCG) in the port of Boston for scheduling their patrols. The system is called PROTECT (Port Resilience Operational / Tactical Enforcement to Combat Terrorism). The USCG s mission includes maritime security of the US coasts, ports, and inland waterways; a security domain that faces increased risks in the context of threats such as terrorism and drug trafficking. Given a particular port and the variety of critical infrastructure that an adversary may attack within the port, USCG conducts patrols to protect this infrastructure; however, while the adversary has the opportunity to observe patrol patterns, limited security resources imply that USCG patrols cannot be at every location 24/7. To assist the USCG in allocating its patrolling resources, PROTECT uses an attacker-defender Stackelberg game framework, with USCG as the defender against terrorist adversaries that conduct surveillance before potentially launching an attack. PROTECT s solution is to typically provide a mixed strategy, i.e. randomized patrol patterns taking into account the importance of different targets, and the adversary s surveillance and anticipated reaction to USCG patrols. USCG has termed the deployment of PROTECT in Boston a success, and efforts are underway to test it in the port of New York, with the potential for nationwide deployment. Since February 2012, USCG has been testing patrols provided by PROTECT in the port of New York. The patrols generated by PROTECT for the USCG incorporate multiple defender patrol boats along with scheduling various defender activities to be performed at the different critical infrastructure. We are planning to incorporate various defender types, such as aerial vehicles, to assist in the patrolling schedules, along with Other Government Agencies (OGAs) in generating a patrol schedule that integrates all these aspects in a single system. 3.5 TRUSTS 1. Figure 4 PROTECT is being used in Boston. Figure 5 Extending PROTECT to NY. Building on the success of the previous projects, TRUSTS (Tactical Randomization for Urban Security in Transit Systems) was developed for fare-evasion deterrence in urban transit systems, carried out in collaboration with the Los Angeles Sheriffs Department (LASD). In many urban transit networks Page 8 of 15

including the LA Metro subway system, there are no ticket-checking gates at the stations. In proof-ofpayment transit systems, passengers are legally required to purchase tickets before entering but are not physically forced to do so. Instead, patrol units move about the transit system, inspecting the tickets of passengers, who face fines if caught fare evading. With approximately 80,000 riders using the LA Metro subway system daily, fare evasion can potentially lead to large amount of revenue loss. The LASD deploys patrol units on board trains and at stations for fare-checking and crime-prevention. Our goal is to design randomized patrol strategies that efficiently utilize limited resources to deter fare-evasion. The deterrence of such fines depends on the unpredictability and effectiveness of the patrols. TRUSTS models the problem of computing patrol strategies as a leader-follower Stackelberg game where the objective is to deter fare evasion and hence maximize revenue. This problem differs from previously studied Stackelberg settings in that the leader strategies must satisfy massive temporal and spatial constraints; moreover, unlike in these counterterrorism-motivated Stackelberg applications, a large fraction of the ridership might realistically consider fare evasion, and so the number of followers is potentially huge. 3.6 Beyond ARMOR/IRIS/GUARDS/PROTECT/TRUSTS There are many other security agencies in the United States and beyond that have expressed an interest in using the Stackelberg game model for improving their operations. One application might be protecting important locations in a city by setting up randomized checkpoints throughout the city, e.g following the devastating attacks in November 2008, Police in Mumbai set up randomized checkpoints throughout the road networks in the city to try to protect the city. Furthermore, while counter-terrorism has remained a key focus of the work so far, the new projects are now extending the application arena to include crime suppression and other objectives. For example, one such application might be improved distribution of patrols throughout forests in order to effectively limit extraction from illegal extractors; yet another one might be randomized checking to support food distribution networks of charity organizations. Other such applications are being discussed. 4 Collaborative Projects From the very beginning, all of our projects, ARMOR, IRIS, GUARDS, PROTECT, and TRUSTS, required extensive collaboration with security agencies. Indeed, we have deployed the ARMOR- Checkpoints and ARMOR-K9 in collaboration with the Los Angeles World Airport (LAWA) police. We have had a close collaboration with Federal Air Marshals (FAMs) for IRIS, with the TSA for GUARDS, the Coast Guard for PROTECT, and the Los Angeles Sheriffs Department for TRUSTS. For PROTECT, we have continued to visit United States Coast Guard headquarters, and hosted their visits to USC. 5 Research Products Research Products (Please detail below) # 5a # of peer-reviewed journal reports published 11 5a # of peer-reviewed journal reports accepted for publication 5a # of non-peer reviewed publications and reports 5a # of scholarly journal citations of published reports >350 5b # of scholarly presentations (conferences, workshops, seminars) 5b # of outreach presentations (non-technical groups, general public) 5c # of products delivered to DHS, other Federal agencies, or State/Local 4 Page 9 of 15

Research Area Referred Not Referred PDF Available for DHS 5c # of patents filed 2 5c # of patents issued 5c # of products in commercialization pipeline (products not yet to market) 5c # of products introduced to market 5.1 Publications and Reports CREATE PUBLICATIONS 1. E. Shieh, R. Yang, B. An, M. Tambe, C. Baldwin, J. DiRenzo, B. Maule, G. Meyer PROTECT: A Deployed Game Theoretic System to Protect the Ports of the United States In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS)(Innovative applications track), Best Paper Award, Innovative Applications, June 2012. 2. Z. Yin, A. Jiang, M.P. Johnson, M. Tambe, C. Kiekintveld, J.P. Sullivan, T. Sandholm, K. LeytonBrown TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems In Proceedings of the Conference on Innovative Applications of Artificial Intelligence (IAAI), July 2012. 3. B. An, E. Shieh, C. Kiekintveld, Y. Vorobeychik, D. Kempe, S. Singh, M. Tambe Security Games with Limited Surveillance In Proceedings of the Conference on Artificial Intelligence (AAAI), July 2012. 4. J. Tsai, T. Nguyen, M. Tambe Security Games for Controlling Contagion In Proceedings of the Conference on Artificial Intelligence (AAAI), July 2012. 5. M. Jain, K. Leyton-Brown, M. Tambe The Deployment to Saturation Ratio in Security Games In Proceedings of the Conference on Artificial Intelligence (AAAI), July 2012. 6. E. Shieh, R. Yang, B. An, M. Tambe, C. Baldwin, J. DiRenzo, B. Maule, G. Meyer PROTECT: An Application of Computational Game Theory for the Security of the Ports of the United States In Proceedings of the conference on Artificial Intelligence (AAAI) (Spotlight track), July 2012. 7. J. Pita, R. Maheswaran, M. Tambe, S. Kraus A Robust Approach to Addressing Human Adversaries in Security Games In Proceedings of the European Conference on Artificial Intelligence (ECAI), August 2012. 8. J. Tsai, E. Bowring, S. Marsella, W. Wood, M. Tambe Emotional Contagion with Virtual Characters In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2012. 9. J. Pita, R. John, R. Yang, R. Maheswaran, S. Kraus, M. Tambe A Robust Approach to Addressing Human Adversaries in Security Games In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), June 2012. 10. J. Tsai, E. Bowring, S. Marsella, W. Wood, M. Tambe A Study of Emotional Contagion with Virtual Characters In Proceedings of the International Conference on Intelligent Virtual Agents (IVA), September 2012. RM x X RM x X RM x X RM x X RM x X RM x X RM x x RM x x RM x x RM x x 11. M. Tambe, M. Jain, J. Pita, A. Jiang Game Theory for Security: Key RM x Page 10 of 15

Research Area Referred Not Referred PDF Available for DHS CREATE PUBLICATIONS Algorithmic Principles, Deployed Systems, Lessons Learned 50th Annual Allerton Conference on Communication, Control, and Computing, 2012. 5.2 Presentations 1. E. Shieh, R. Yang, B. An, M. Tambe, C. Baldwin, J. DiRenzo, B. Maule, G. Meyer PROTECT: A Deployed Game Theoretic System to Protect the Ports of the United States In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS)(Innovative applications track), Best Paper Award, Innovative Applications, June 2012. 2. Z. Yin, A. Jiang, M.P. Johnson, M. Tambe, C. Kiekintveld, J.P. Sullivan, T. Sandholm, K. LeytonBrown TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems In Proceedings of the Conference on Innovative Applications of Artificial Intelligence (IAAI), July 2012. 3. B. An, E. Shieh, C. Kiekintveld, Y. Vorobeychik, D. Kempe, S. Singh, M. Tambe Security Games with Limited Surveillance In Proceedings of the Conference on Artificial Intelligence (AAAI), July 2012. 4. J. Tsai, T. Nguyen, M. Tambe Security Games for Controlling Contagion In Proceedings of the Conference on Artificial Intelligence (AAAI), July 2012. 5. M. Jain, K. Leyton-Brown, M. Tambe The Deployment to Saturation Ratio in Security Games In Proceedings of the Conference on Artificial Intelligence (AAAI), July 2012. 6. E. Shieh, R. Yang, B. An, M. Tambe, C. Baldwin, J. DiRenzo, B. Maule, G. Meyer PROTECT: An Application of Computational Game Theory for the Security of the Ports of the United States In Proceedings of the conference on Artificial Intelligence (AAAI) (Spotlight track), July 2012. 7. J. Pita, R. Maheswaran, M. Tambe, S. Kraus A Robust Approach to Addressing Human Adversaries in Security Games In Proceedings of the European Conference on Artificial Intelligence (ECAI), August 2012. 8. M. Tambe Game theory for Security: Key Algorithmic Principles, Deployed Systems, Lessons Learned 2012 Conference on Homeland Security Modeling and Simulation (HLSMS12) 9. M. Tambe Game theory for Security: Key Algorithmic Principles, Deployed Systems, Lessons Learned Workshop on Safety, Security for Critical Infrastructure (SS4CI), Prague, 2012 10. M. Tambe Game theory for Security: Key Algorithmic Principles, Deployed Systems, Lessons Learned Workshop on Games, Networks and Markets, Microsoft Research, Cambridge, UK 2012 Page 11 of 15

11. M. Tambe Game theory and Human Behavior: Challenges in Security AAMAS workshop on Human-Agent Interaction Design and Models, 2012 12. M. Tambe Game theory for security: A real-world challenge problem for multiagent systems and beyond AAAI Spring Symposium on AI, The Fundamental Social Aggregation Challenge, and the Autonomy of Hybrid Agent Groups, 2012 Page 12 of 15

5.3 Software Tools and Products The following softwares have been delivered; updates to the softwares continue to be made. SOFTWARE PRODUCTS Project Leader(s) Date Delivered Item Agency Receiving Product Agency POC Commercialization Status Tambe 3-2011 PROTECT Coast Guard Craig Baldwin delivered Tambe 5-2010 GUARDS TSA Erin Steigerwald delivered Tambe 8-2009 IRIS FAMS James Curren delivered; pipeline Tambe 2-2008 ARMOR LAWA Police Ernest Cruz delivered; pipeline Tambe 8-2007 ARMOR LAWA Police James Butts delivered; pipeline 6 Education Education Initiatives (Please detail below) # # of students supported (funded by CREATE) 5 # of students involved (funded by CREATE + any other programs) # of students graduated # of contacts with DHS, other Federal agencies, or State/Local (committees) # of existing courses modified with new material # of new courses developed # of new certificate programs developed # of new degree programs developed Education Activities Professional Development, Internship and Summer Research Opportunities for Students Deliberate Mentorship Activities of Students and Post-docs Interactions with K12 teachers and/or students Description Summer internship for You Zhou in helping with the IRIS project for FAMS. Weekly meetings and annual team-building retreat for PhD students and postdoctoral researchers. All students/postdoctoral researchers involved: Postdoctoral researchers: Bo An Albert Jiang Page 13 of 15

PhD students: Manish Jain James Pita Eric Shieh Jason Tsai Zhengyu Yin Master students: Parth Shah You Zhou 7 Outreach Membership in DHS Related Committees Testimonies o Testimony by Robert S. Bray, Assistant Administrator, T.S.A. before the United States House of Representatives, Transportation Security Subcommittee, Homeland Security Committee. February 15, 2012: Testimony by Robert S. Bray, http://teamcore.usc.edu/news/testimony_2012.pdf Hill Visits Visits to/meetings with DHS on behalf of CREATE Visits to/meetings with Other Govt Agencies on behalf of CREATE Media Coverage o o o o Coast Guard Outlook Magazine, Aug 7, 2012: CREATE's ARMOR-PROTECT Featured in Coast Guard Outlook Magazine, http://teamcore.usc.edu/news/newsoutlook.pdf Airport Technology Article, July 26, 2012: Game theory: introducing randomness to airport security, http://teamcore.usc.edu/news/airporttechnews.pdf DefenseMediaNetwork Article, July 10, 2012: The Port Resiliency for Operational/Tactical Enforcement to Combat Terrorism Model, http://www.defensemedianetwork.com/stories/the-port-resiliency-foroperationaltactical-enforcement-to-combat-terrorism-model/ CREATE News Article, April 18, 2012: New Book "Security and Game Theory" by CREATE's Milind Tambe, http://teamcore.usc.edu/news/new_book_security_game_theory.pdf Page 14 of 15

o Viterbi News Article, April 06, 2012: Viterbi-led Initiative in Game Theory and Human Behavior Crosses Multiple Disciplinary Lines, http://teamcore.usc.edu/news/viterbi_led_initiative_gthb.pdf External Partnerships/Relationships Established Outreach Event Presentations and/or Attendance Events Organized or Hosted on behalf of CREATE o Game Theory for Security Tutorial. CREATE Seminar given by Milind Tambe, Albert Jiang, and Manish Jain. August 2012. http://create.usc.edu/2012/09/game_theory_tutorial_seminar.html New Marketing Materials (brochures, fact sheets, websites please share a copy) Seminars or Lectures (if videotaped, please provide video link) o Game Theory for Security Tutorial. CREATE Seminar given by Milind Tambe, Albert Jiang, and Manish Jain. August 2012. http://create.usc.edu/2012/09/game_theory_tutorial_seminar.html Page 15 of 15