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Clues to preventing terrorism hidden within Web use, e-mail, inspection records and communication

Profiles of four students in multiple disciplines seeking to prevent terrorism

(July 10, 2007)

Steven Bethard – As a computer science and cognitive science Ph.D. candidate at the University of Colorado at Boulder, Bethard, also a DHS dissertation grant recipient, is developing machine learning methods. The machines, e.g. search engines, are programmed as to how best to identify temporal and causal relations in text so that timelines can be automatically generated. Without this programming, the typical search engine or commercial computer application will view bodies of text as simply a collection of words. Bethard sees information analysts as key beneficiaries of his research. He anticipates graduating from Colorado-Boulder in December 2007.

Peter Frazier – A Ph.D. candidate in Princeton University’s Department of Operations Research and Financial Engineering, Frazier is “researching how we can collect information most efficiently.” Taking the form of savings in time, money and resources, this savings occurs through Frazier’s management of stochastic optimization problems. By modeling relevant information about a situation across relevant points in time, e.g. choosing which cargo containers to inspect as they enter a port, probabilities can be charted. Frazier is also using mathematical frameworks for scenarios such as the placement of radiological, chemical and nuclear detectors in the most appropriate spots in a location to collect information that would be of the highest value versus information that is irrelevant. An example is the collection of data on potentially harmful and human-introducted sources of radiation in a specific location less-threatening natural sources of radiation.

Lara Gunther – As a former DHS Scholar, Gunther worked with the START DHS Center of Excellence while completing her B.A. degree in criminal justice from the University of West Florida. Gunther also earned a minor in social welfare. Her work with START included a partnership with the FBI and sought to extract meaning from the analysis of al’Quaida transcripts and speeches. A critical outcome of her research is the advancement of the FBI’s ability to predict al’Quaida terrorist events and the nature of those events. Gunther is currently exploring a variety of employment options.

Yihua Wu – A student at the Center for Dynamic Data Analysis (DyDAn) at Rutgers University, Wu’s research studies communication events between individuals and within online networks representing these occurences through graphs. Natural questions within her research arise such as, “Has an individual suddenly altered her communication patterns?,” and “Can we detect the same individual using multiple identities?” Such questions can be answered using appropriate signature-based methods on graphs that permit Wu to analyze one’s online activities. Applications of her work include improved cybersecurity.