Intelligence Analysis for Homeland Security

CREATE Research Archive Research Project Summaries 1-1-2010 Intelligence Analysis for Homeland Security Gary M. Shiffman Georgetown University, gms2...
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CREATE Research Archive Research Project Summaries

1-1-2010

Intelligence Analysis for Homeland Security Gary M. Shiffman Georgetown University, [email protected]

Robin Dillon-Merrill Georgetown University, [email protected]

Genevieve Lester Georgetown University

Catherine H. Tinsley Georgetown University, [email protected]

Follow this and additional works at: http://research.create.usc.edu/project_summaries Recommended Citation Shiffman, Gary M.; Dillon-Merrill, Robin; Lester, Genevieve; and Tinsley, Catherine H., "Intelligence Analysis for Homeland Security" (2010). Research Project Summaries. Paper 7. http://research.create.usc.edu/project_summaries/7

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 [email protected].

Intelligence Analysis for Homeland Security Gary M. Shiffman, Georgetown University Center for Peace and Security Studies (CPASS) [email protected]

Other Contributing Investigators: Robin Dillon-Merrill, Georgetown University School of Business Genevieve Lester, CPASS Catherine Tinsley, CPASS 1. 2. 2.1. 2.2. 3. 3.1. 3.2. 4. 5. 5.1. 5.2. 6. 7.

Executive Summary .............................................................................................................................................1 Research Accomplishments .................................................................................................................................2 Terrorism Risk Factors .....................................................................................................................................2 Using Multi-attribute Utility models to Structure Domestic Intelligence Policy..............................................2 Applied Relevance ...............................................................................................................................................4 Improved risk-based prioritization frameworks ...............................................................................................4 Communicating Domestic Intelligence Policy to Stakeholders ........................................................................4 Collaborative Projects ..........................................................................................................................................5 Research Products ................................................................................................................................................5 Publications and Reports ..................................................................................................................................5 Presentations .....................................................................................................................................................6 Education and Outreach Products ........................................................................................................................7 Membership in Major DHS Related Committees ................................................................................................8

1. Executive Summary The research at Georgetown has focused on two specific projects: Terrorist Risk Factors and Using Multiattribute Utility models to Structure Domestic Intelligence Policy. The first project, Terrorist Risk Factors (TRF) is led by Gary Shiffman, Director, Homeland Security Studies, CPASS, Georgetown University, in collaboration with Eli Berman, IGCC, University of California. The TRF project is working to develop innovative and original methodologies for assessing risk in homeland security environments. The project is working on outreach to subject matter expert communities, both on the law enforcement/civil as well as military/intelligence communities, writing and editing a journal article for submission to peer-reviewed journals, and mentoring graduate students. (Keywords: terrorist objective functions, economic and decision models of terrorist enterprises) The second project, Using Multi-attribute Utility models to Structure Domestic Intelligence Policy (MAU), is led by Robin Dillon-Merrill, Associate Professor in the McDonough School of Business as Georgetown University with Georgetown colleagues, Genevieve Lester, and Catherine Tinsley. This project is collaborative with Richard John at USC. The MAU project is contributing to the field of Domestic Intelligence research by quantifying major stakeholder groups’ objectives and preferences regarding domestic intelligence activities. The team has collected survey data from over 150 participants who completed a multi-attribute assessment model that considered several domestic intelligence policy alternatives. The participants were students, researchers from the DHS community, and police officers. (Keywords: value focused thinking, values hierarchy, domestic intelligence)

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 award number 2010-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, or CREATE.

2. Research Accomplishments

2.1. Terrorism Risk Factors After September 11, 2001, U.S. border enforcement authorities defaulted to and adapted existing tools to respond to the newly prioritized terrorist threat. Given that 1.1 million people enter the U.S. daily, 700,000 of which are foreign nationals, border authorities must constantly refine risk-based methodologies to address the newly prioritized counterterrorism mission while facilitating the normal flow of goods and people across the border. To do this, they evolved risk-based targeting models built for criminal and immigration threats however, room for improvement still exists. This project explored two rational choice models developed as part of other funded research efforts at CREATE to the University of California and Princeton University. The models applied to a homeland security context helped to explain individual motivations for joining and supporting terrorist and insurgent organizations. Applied properly, we demonstrated that social science algorithms can help to generate innovations in the DHS risk-based targeting methods to both increase border security and streamline the process for legitimate travelers and cargo. 2.2. Using Multi-attribute Utility models to Structure Domestic Intelligence Policy This project seeks to understand the public’s beliefs about the consequences of different domestic intelligence alternatives with respect to value relevant attributes (such as cost or effectiveness) as well as value trade-offs for those same attributes. Understanding these beliefs and values is important to developing a sustainable and acceptable public policy, because domestic intelligence gathering lies at the nexus of security and public expectations of privacy in a democracy. The model captured both respondents’ beliefs about the consequences resulting from policy implementation, e.g., cost, effectiveness, and respondents’ value tradeoffs (e.g., the exchange-rate between effectiveness and intrusiveness). Differentiating between disagreements related to beliefs about consequences versus disagreements about value priorities is crucial for understanding the genesis of the debate surrounding new policy initiatives and hence for constructing effective risk communication messages to the public. The figure below shows the MAU model.

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Best Domestic Intelligence Policy Max Effectiveness

Min Intrusiveness

Min Cost

Max Trust & Credibility

Max Quality of Process

Deterrent Effect

Equity in Impacts & Benefits

Direct

Management of Data

Congressional Oversight

Plans Thwarted

Transparency

Indirect

State & Local Involvement

Open Debate

Criminals Captured

Open Source

Terrorists Captured

Voluntary

Low False Positive Rate

Impact to Freedom

Highest Threats Targeted

What is clear from our results is that respondents do not apply some overarching “rule of thumb” to the assessments, i.e., “given my political orientation, all alternatives are bad.” Respondents clearly treat each alternative uniquely when considering how an alternative would score on an objective. We did see some “halo” effect for respondents’ beliefs about how well each alternative delivers, where unacceptable alternatives were also perceived to be lower on most or almost all of the objectives. The benefit of our model is that we can analyze and explore why people have different perceptions of acceptability and can identify whether these differences are because of differences in value tradeoffs among fundamental objectives or their beliefs about how the alternative performs on the various objectives (i.e., effectiveness, intrusiveness, cost, etc.). Our data show that it is some of both factors. We recognize that most past policy work that utilized value models focused on differences in weights as the source of disagreements. If there are differences in beliefs about the consequences of alternatives on objectives, Ward Edwards recommends “asking only the best available expert for each dimension to make judgments about that dimension.” What is insightful about our research is that while a right answer for the consequences probably exists, in most cases, people will rely on their perceptions of the consequences when formulating their feelings toward alternatives. Insights about why people have different feelings about acceptability of policy alternatives can potentially inform decision makers and aid in the construction of a risk communication strategy. It is especially

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important for the alternatives that are not broadly acceptable (undercover federal officials at religious and civic group meetings, expanded authority to stop and search vehicles, and federal officials reviewing and compiling personal communications), that the risk communication strategy should emphasize the strengths of the alternative, especially to convince people that the policy is effective and would be implemented with a process of high quality, accountability, and transparency. Our data suggests the best public awareness messages should be focused on the beliefs about each alternative’s ability to deliver on objectives rather than on a debate about the relative importance of different values such as security and privacy. 3. Applied Relevance

3.1. Improved risk-based prioritization frameworks September 11, 2001, catalyzed a focused shift from the long history of border programs prioritizing illegal immigration and criminal activity, to terrorism as the priority mission. In the weeks following the 9/11 terrorist attacks, the then-U.S. Customs Service changed its priority mission. This meant that in addition to the primary traditional mission of border security CBP’s priority mission became that of identifying terrorists or terrorist weapons crossing the U.S. border. The nature of this new mission requires constant innovation and evolution. Techniques and procedures that were once aimed primarily at criminals and illegal immigrants have to be modified to target international terrorists as well. By revisiting the existing border security programs, CBP’s screening techniques can confine the trend of effectiveness, specifically in the context of anti-terrorism, through refining the variables used for riskbased targeting. Risk-based targeting remains the core of DHS efforts to facilitate trade and travel while maintaining the security of the United States. The success of DHS, and in particular CBP, depends on its ability to identify which people entering the United States likely to pose a terrorist, criminal, or immigration threat. Interrogating 100% of travelers and cargo upon entry to the U.S. is not only impractical, but also imprecise. Rather, DHS relies on algorithms that input available information about each person into decision-improvement tools that indicate how likely they are to pose a threat to the security of the U.S. These algorithms can be improved in two ways: by finding new variables which are correlated with a higher threat probability, and by enhancing existing variables to identify threats more accurately. To improve these algorithms, social science models of counterterrorism that explore the motivations of individuals for joining terrorist and criminal organizations. Applied appropriately, many existing models provide theoretical implications for new risk factors that should be helpful in producing innovations in the United States’ risk-based homeland security screening methods.

3.2. Communicating Domestic Intelligence Policy to Stakeholders In the fall of 2010 as the holiday travel period approached, there was increasing scrutiny and criticism in the media of the full-body scanners being deployed in US airports. This criticism included Ralph Nader and the Electronic Privacy Information Center launching a campaign against the full-body scanners arguing that the machines are easily hackable, store nude pictures of their subjects, pose a radiation risk,

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and don’t work all that well. Criticism also came from major unions representing airline pilots that recommended that pilots refuse to use the screeners. Our research demonstrates the feasibility of eliciting preference models from individuals and shows how this method can help identify the locus of possible disagreements among individuals when disagreements exist among policy options. Our modeling approach and results offer organizations such as the Department of Homeland Security (DHS) insights into the debate surrounding new policy initiatives, particularly those potentially requiring sensitive value tradeoffs. In the particular case of the full-body scanners, the DHS/TSA should be emphasizing to the public the effectiveness of the scanners (which it does not currently seem to be doing).

4. Collaborative Projects Currently, both projects described here are collaborative with other partners at CREATE.

5. Research Products Research Products (Please detail below) 5a # of peer-reviewed journal reports published 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 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 5c # of patents filed 5c # of patents issued 5c # of products in commercialization pipeline (products not yet to market) 5c # of products introduced to market ** The paper documenting the MAU project is currently under 3rd round review at Risk Analysis.

# **

4 3

Referred

1.

Gary M. Shiffman and Jonathan Hoffman, The Department of Homeland Security: Chief of Coordination, The National Security Enterprise: Navigating the Labyrinth, Edited by Roger Z. George, Harvey Rishikof, Foreword by Lt. Gen. Brent Scowcroft, USAF (Ret), Georgetown University Press, 2011.

RA

X

2.

Robin L. Dillon, Genevieve Lester, Richard John, Catherine Tinsley, Differentiating Conflicts in Beliefs vs. Value Trade-offs in the Domestic Intelligence Policy Debate, prepared for Risk Analysis, under 3rd round review

RA

X

CREATE PUBLICATIONS Last Name, First Name – Name of University

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Not Referred

Research Area

5.1. Publications and Reports

Not Referred

Referred

Research Area

CREATE PUBLICATIONS 3.

Gary M. Shiffman, Nicolle Sciara-Rippeon, and Michael Gee, Managing the Dots: The Challenges of Intelligence Sharing for the Homeland Security Enterprise, Center for Peace and Security Studies monograph, February 2010.

RA

X

4.

Gary M. Shiffman, Nicolle Sciara-Rippeon, and Michael Gee, In Search of Magic Waters: Overcoming Information Sharing Obstacles for the Homeland Security Enterprise, Center for Peace and Security Studies monograph, February 2010.

RA

X

5.2. Presentations 1.

Shiffman, Gary M, “Terrorist Risk Factors,” presentation to the Council on Foreign Relations, homeland security subject matter expert audience, Washington, DC February, 2010.

2.

Shiffman, Gary M, International Institute for Counterterrorism conference Herzlya Israel, Sept 12-15, 2010.

3.

Shiffman, Gary M, “Costs and Benefits of Homeland Security,” Summer Continuing Studies (90 high schools students from around the country), Washington, DC, July 26, 2010.

4.

Shiffman, Gary M, “Teaching Homeland Security—Initiatives at Georgetown University CPASS,” presentation to 200 post-secondary educators on curriculum development, Washington, DC February, 2010.

5.

Shiffman, Gary M, In Search of Magic Waters Conference, Oct 2009.

6.

Shiffman, Gary M, Homeland Defense and Security Education Summit co-Host, Feb 24-25, 2010

7.

Shiffman, Gary M, DHS Seminar on Regulations, sponsored by S&T, Nov 2011 at American University, Hosted by Gary Becker

8.

Dillon, Robin, “Framing Decisions: Using Multi-Attribute Utility Models to Structure Domestic Intelligence Policy”, CREATE Risk Perception Conference, LA, March 5-6

9.

Lester, Genevieve, “Framing Decisions: Using MAU to Structure Domestic Intelligence Policy,” International Studies Association Annual Conference, New Orleans, LA, 18 February 2010. Panel: Practitioner - Academic Interaction in Threat/Risk Analysis (Note ISA presentation while at a scholarly conference was part of a panel specifically designated for the Practitioner)

10. Dillon, Robin & Richard John (presenter), “Using MAU to Structure Domestic Intelligence Policy” INFORMS, Austin TX, November 8, 2010 11. Dillon, Robin & Richard John (presenter), “Using MAU to Structure Domestic Intelligence Policy” Society of Judgment and Decision Making, St. Louis, November 21, 2010

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6. Education and Outreach Products Education and Outreach Initiatives (Please detail below) # of students supported (funded by CREATE) # 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 * we created a homeland security concentration within our MA program. Last Name

First Name

University

1.

Kizitlan

Berfu

Georgetown

2.

Co

Wilson

Georgetown

3.

Solamani

Roya

Georgetown

4.

Burkart

Meredith

Georgetown

5.

Pandya

Harsh

Georgetown

6.

Gee

Michael

Georgetown

7.

Brooks

Hugh

Georgetown

8.

Ghali

Holly

Georgetown

9.

Khadka

Prabin

Georgetown

10.

Brooks

Hugh

Georgetown

11.

Gupta

Ravi

Georgetown

12.

Kisselburg

Alex

Georgetown

13.

Counihan

Michael

Georgetown

14.

Beane

Sarah

Georgetown

15.

Lim

Danile

Georgetown

School

Department

School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service School of Foreign Service

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Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program Security Studies Program

# 4 5 2 At least 6 2

1*

Degree MA MA MA

Research Area Domestic Intelligence “Who’s Dots” seminar “Who’s Dots” seminar

Funded? Y Y Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counterinsurgency / Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

MA

Counter Terrorism

Y

7. Membership in Major DHS Related Committees Robin Dillon-Merrill, Committee on Risk-Based Approaches for Securing the DOE Nuclear Weapons Complex, National Research Council Gary Shiffman, Board of Advisors, DHS/BORDERS Center of Excellence, lead institution: University of Arizona Catherine Tinsley, Committee on Behavioral and Social Science Research to Improve Intelligence Analysis for National Security, National Research Council. Catherine Tinsley, Committee on Unifying Social Frameworks, Board on Behavioral, Cognitive, and Sensory Sciences Division of Behavioral and Social Sciences and Education, National Research Council.

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