25 Pages Posted: 5 Apr 2008 Last revised: 27 Feb 2014
The 9/11 terrorists, before their deadly attacks, sought invisibility through integration into the society they hoped to destroy. In a similar fashion, the terrorists who carried out subsequent attacks in Madrid and London attempted to blend into their host lands. This strategy has forced governments, including the United States, to rethink counterterrorism strategies and tools.
One of the current favored strategies involves data mining. In its pattern-based variant, data mining searches select individuals for scrutiny by analyzing large data sets for suspicious data linkages and patterns. Because terrorists do not stand out, intelligence and law enforcement agents want to do more than rely exclusively on investigations of known suspects. The new goal is to search for a pattern or signature in massive amounts of transaction data.
This Article begins by examining governmental data mining. In Part II, this Article reviews widely held views about the necessary safeguards for the use of data mining. In Part III, this Article considers dataveillance by private corporations and how they have compiled rich collections of information gathered online in the absence of a robust legal framework that might help preserve online privacy.
This Article then discusses some of the techniques that individuals can employ to mask their online activity as well as existing and emerging technological approaches to preventing the private sector or government from linking their personal information and tracing their activities. This Article concludes by briefly considering three topics: (1) whether and how to regulate the potential impact of identity management systems on counterterrorism efforts; (2) the requirements of transparency and understanding of the underlying models used in either data mining or identity management systems as a necessary prelude to the creation of rules on appropriate access and use; and (3) the need for research in several further areas.
Suggested Citation: Suggested Citation
Rubinstein, Ira and Lee, Ronald D. and Schwartz, Paul M., Data Mining and Internet Profiling: Emerging Regulatory and Technological Approaches. University of Chicago Law Review, Vol. 75, p. 261, 2008; UC Berkeley Public Law Research Paper No. 1116728. Available at SSRN: https://ssrn.com/abstract=1116728