Project on Data Mining, Automated Data Analysis, and Computational Social Science

Research Project Purpose:

To examine the policy and legal implications of using data mining, automated data analysis, and computational social science technologies in law enforcement and national security applications. To understand and describe the social and political implications of a "data processing model" of law enforcement and security.

Overview:

In the context of law enforcement and security, automated data analysis is intended to produce information or knowledge (i.e., actionable intelligence) from low-level data by turning low-level data, usually too voluminous or granular to understand directly, into higher forms (information or knowledge) that might be more compact (for example, a summary), more abstract (for example, a descriptive model), or more useful (for example, a predictive model). Automated data matching or monitoring is intended to spot patterns, deviations, or anomolies in data sets or data flows in order to focus law enforcement or security resources on data subjects of interest.

There are three distinct applications for automated analysis in the context of law enforcement and national security security:

• first, subject-oriented link analysis, that is, automated analysis to learn more about a particular data subject, their relationships, associations and actions;

• second, pattern-analysis (including traffic analysis), that is, automated analysis to develop a descriptive or predictive model based on discovered patterns in datasets or data flows; and,

• third, pattern-matching or filtering, that is, automated analysis using a descriptive or predictive model (whether or not the model or filter itself is developed through automated analysis) against datasets or data flows to identify other related (or “like”) data subjects (people, places, things, relationships, etc.), or to identify deviations or anomolies from expected patterns.

The combination of mathematics, statistics, economics, political science, cultural anthropology, sociology, psychology, psychiatry, neuroscience, criminology, and other social sciences with automated data analysis techniques such as federated search and retrieval, filtering, visualization, knowledge extraction, modeling, and simulation — together referred to expansively as "data mining" for purposes of this project — enable the development and application of nonlinear, nondeterministic theories and models of complex human phenomena at all scales to social governance and control problems, including law enforcement and national security.

These technologies are becoming important tools of social risk management in the emerging cybernetic society in which the main venue for social, economic, and political interaction and influence is the global electronic communications and data network.

The development and application of automated monitoring and analysis technologies is accelerating the ongoing transformation of modern information-based societies from a notional Beccarian ("punishment") model of social order based on accountability for deviant actions after they occur, first, to a Foucauldian ("disciplinary") model based on authorization, preemption, and general social compliance through ubiquitous preventative surveillance and control through system constraints and, ultimately, to a complex Deleuzian ("control") model based increasingly on seduction and enticement through manipulation of opportunity and desire rather than just coercion or constraint — the omniveillant society.

In this emergent social model, security services are not geared toward policing through arrest and prosecution, but initially to risk management through surveillance, information exchange, auditing, communication, and classification, and, ultimately, to preemptive social control through engineered outcomes.

This research project examines the policy and legal implications of applying such technologies to law enforcement and national security problems, including counterterrorism intelligence, cybersecurity, and terrorist attack preemption, among others.

An underlying premise of this research project is that uses in this context involve the forward problem of discovering valid threat signals and the inverse problem of preempting hostile or criminal acts by monitoring for and spotting those signatures from among significant background data volumes while ensuring system functionality (low operational friction) and while maintaining high degrees of freedom (including personal political autonomy, privacy, civil liberties, and, where appropriate, secrecy and anonymity).

Keywords:
data mining, automated data analysis, knowledge discovery, link analysis, traffic analysis, pattern analysis, computational social science, counterterrorism, national security, domestic security, homeland security, law enforcement, foreign intelligence, criminal inteligence, cyber-security, network security, electronic surveillance, dataveillance, intelligence informatics, cybernetics, civil liberties, privacy, search and seizure, fourth amendment, information society

Page URL: <data-mining-program.info>

Upcoming Events:

Kim Taipale to present Predictive Analytics and Perception Shaping at EU-ITA, Jun. 8-9, 2011.

Kim Taipale to present Behavioral Tracking and Social Control at GISP Forum, November 28, 2011.

Recent Events:

Kim Taipale participated in Addressing Complex Problems, Highlands Forum XLIII (OSD), Phoenix, Arizona (Nov. 7-9, 2010).

Kim Taipale participated in No More Secrets: National Security Strategies for a Transparent World sponsored by the ABA Standing Committee on Law and National Security, the Office of the National Counterintelligence Executive, and the National Strategy Forum, Wash., DC (June 29, 2010).

Kim Taipale discussed Cyber Security, Cyber Warfare, and National Security at "National Security Challenges and the Obama Administration", Duke University School of Law, Durham, NC (Apr. 15-16, 2010).

Kim Taipale discussed Cyberspace and the Fourth Amendment at the U.S. Court of Appeals for the Armed Forces 2010 Annual Judicial Conference, Washington, DC (Mar. 10-11, 2010).

Kim Taipale discussed "The Rise of America’s Surveillance State" with author Shane Harris at The Brookings Institution, Wash. DC (Mar. 11, 2010).

Kim Taipale participated in Extreme Inference: Implications of Data Intensive Advanced Correlation Techniques, Eighteenth Annual Aspen Institute Roundtable on Information Technology (Aug. 4-7, 2009).

Related Congressional Testimony:

K. A. Taipale, The Privacy Implications of Government Data Mining Programs, Testimony before the U.S. Senate Committee on the Judiciary, Washington, DC (Jan. 10, 2007). [HTML] [PDF]

Background material:

Data Mining: Background Materials Prepared for the Committee on the Technical and Privacy Dimensions of Information for Terrorism Prevention and Other National Goals, The National Academies, Selected Writings of K. A. Taipale, Center for Advanced Studies in Sci. & Tech. Pol’y (Apr. 2006). Download Version 1.6 (3.2 MB PDF).

Selected CAS Articles:

K. A. Taipale, Data Mining and Domestic Security: Connecting the Dots to Make Sense of Data, 5 Columbia Sci. & Tech. L. Rev. 2 (Dec. 2003).

K. A. Taipale, Technology, Security and Privacy: The Fear of Frankenstein, the Myth of Privacy and the Lessons of King Ludd, 7 Yale J. L. & Tech. 123-201; 9 Intl. J. Comm. L. & Pol'y 8 (Mar. 2004) (See section on "TECHNOLOGIES OF DATA AGGREGATION AND ANALYSIS" p. 162-172)

K. A. Taipale, The Trusted System Problem: Security Envelopes, Statistical Threat Analysis, and the Presumption of Innocence, Homeland Security, IEEE Intelligent Systems, V.20 No.5, pp 80-83 (Sep./Oct. 2005).

K. A. Taipale, Whispering Wires and Warrantless Wiretaps: Data Mining and Foreign Intelligence Surveillance, NYU Rev. L. & Security, No. VII Supl. (Spring 2006) (See section on "Automated analysis: data mining and traffic analysis").

K. A. Taipale, Why Can't We All Get Along? How Technology, Security and Privacy Can Co-exist in a Digital World, in Cybercrime and Digital Law Enforcement, Yale Information Society Project series, (Jack Balkin, et al., eds., NYU Press, 2007).

K. A. Taipale, The Ear of Dionysus: Rethinking Foreign Intelligence Surveillance, 9 Yale J. L. & Tech. 128-161 (Spring 2007) (See section on "AUTOMATED ANALYSIS: CONTENT FILTERING, TRAFFIC ANALYSIS, AND LINK OR PATTERN ANALYSIS" p. 150-156).

Other References (data mining):

ISAT 2002 Study, Security with Privacy (Dec. 2002). (PDF)

Paul Rosenzweig, Proposals for Implementing the Terrorism Information Awareness System, Legal Memorandum No. 8, Heritage Foundation (Aug. 2003) 2 Geo. J. L. & Pub. Pol’y 169 (2004).

Department of Defense (DOD) Technology and Privacy Advisory Committee (TAPAC), Safeguarding Privacy in the Fight Against Terror, Final Report (Mar. 2004). (PDF from CDT)

Mary DeRosa, Data Mining and Data Analysis for Counterterrorism, CSIS Press (Mar. 2004).

Charles Weiss, The Coming Technology of Knowledge Discovery: A Final Blow to Privacy Protection? 2004 U. Ill. J. L. Tech. & Pol’y 253 (2004).

ABA SCL&NS, Cantigny Principles on Technology, Terrorism, and Privacy, Nat. Sec. Law Report (Feb. 2005).

Daniel J. Steinbock, Data Matching, Data Mining, and Due Process, 40 Georgia L. Rev. (2005). (SSRN)

Fred H. Cate, Legal Standards for Data Mining, in Emergent Information Technologies and Enabling Policies for Counter-Terrorism (Robert Popp and John Yen, eds., IEEE-Wiley Press, Jun. 2006).

Selected Previous CAS Presentations:

K. A. Taipale, Data Mining and Counterterrorism: Methodology and Policy, at "Advancing Analytic Techniques in Counterterrorism Analysis," in Arlington, VA, Aug. 19, 2005.

K. A. Taipale, Emerging Technologies in Security Evaluations, National Science Foundation, Arlington, VA, Jul. 13-14, 2005.

K. A. Taipale, Counterterrorism Technology and Privacy at the ABA Standing Committee on Law and National Security conference "National Security Law in a Changed World: The Fourteenth Annual Review of the Field," Arlington, VA on Nov. 18-19, 2004.

K. A. Taipale, Technology as a Tool to Protect Civil Liberties: Data Mining, Enterprise Architecture, and Civil Liberties, at the Counterterrorism Technology and Privacy Conference, McCormick Tribune Foundation Cantigny Conference Series, ABA Standing Committee on Law and National Security, Jun. 24-25, 2004.

K. A. Taipale, New Tools: Design, Technology, Control, Data Mining and Surveillance at "Digital Cops in Virtual Environment - CyberCrime and Digital Law Enforcement," Yale Law School, Mar. 26-28, 2004.

Selected Related Testimony:

K. A. Taipale, Foreign Intelligence Surveillance Act Reform, Testimony before the House Permanent Select Committee on Intelligence, U.S. House of Representatives, July 19, 2006. [Written Testimony] (see section on automated analysis)

Testimony of Kim Taipale, executive director of the Center for Advanced Studies, Foreign Intelligence Surveillance Modernization: Reconciling Signals Intelligence Activity with Targeted Wiretapping, U.S. Senate Select Committee on Intelligence (SCCI) Hearing on The Foreign Intelligence Modernization Act of 2007, May 1, 2007.

About the Center for Advanced Studies:

The Center for Advanced Studies in Science and Technology Policy is a private, non-partisan research and advisory organization focused on information, technology and national security policy and related issues.

The Center seeks to inform and influence national and international policy- and decision-makers in both the public and private sectors by providing sound, objective analysis and advice, in particular by identifying and articulating issues that lie at the intersection of technologically enabled change and existing practice in policy, law and industry.

The Center has research programs in:

among others [see research programs].

Areas of Focus:

Information Policy: National and domestic security and civil liberties (including privacy), cybersecurity and computer crime, telecommunications and spectrum, intellectual property, innovation and antitrust, internet and free speech. Information policy and free trade, globalization and global security, international jurisdiction, internet governance. Information management, institutional and organizational architecture and business process engineering.

Enabling Technologies: Data aggregation, data integration, data fusion, data analysis, data mining, artificial intelligence, decision support, distributed networks, enterprise architecture, distributed computing, wireless communication, remote sensing, identification, authentication, network and computer security, biometrics, cryptography, rule-based processing, digital rights management, knowledge management.

Security Applications: Foreign intelligence, defense intelligence, counter intelligence, counter insurgency, domestic intelligence, law enforcement, counterterrorism, electronic surveillance, regulatory compliance, corporate and enterprise security, corporate intelligence, competitive intelligence, systems security, cybersecurity, information security, communication security, information assurance, information warfare, information operations, netcentric strategy, environmental monitoring, international relations and global security.