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Penn professor Michael Kearns developed an algorithm to find a middle ground between national security and personal security. 

Photo: Remy Haber

While today’s politicians and lawmakers struggle to find a balance between personal privacy and national security, a Penn professor is working on an answer.

Professor Michael Kearns, national center chair in the Department of Computer and Information Science, just published a paper on a computer algorithm that can use the structure of social networks to target certain individuals or groups — without compromising the privacy of people who are not involved. The algorithm would come with many applications, but Kearns is currently most interested in potential for counterterrorism.

“It’s an algorithm to use the social network to guide the search for some targeted subpopulation, which in the case of the NSA you can think of as some group of terrorists or other bad actors,” Kearns said.

If created, this algorithm could have major implications for the political scene, particularly after former CIA member Edward Snowden’s revelations of the information that the government has kept secret from the public. The algorithm is possibly the only solution developed so far to find a middle ground between national security and personal security.

“Our paper is showing that in a natural setting, there are scenarios where there is a middle ground — where you can say to one part of the population, ‘We are going to protect your privacy, even while we still need to find people with this other property,’” Kearns said.

The basic premise of the algorithm is that the government has a massive amount of cellphone and other social data that links people together in an intricate “social network.” Given this data and some leads on known criminals, the algorithm can track connections that other individuals have had with these people in order to find other likely targets — all without revealing to the government exactly what information it had gone through.

“The basic logic is that terrorists are more likely to talk to other terrorists,” Kearns explained.

By tracking the connections that certain people have with the known “bad actor,” the algorithm could return a list of the most probable other criminals involved without compromising the security of the information that was used to target these people or the security of innocents not involved whose information was also searched. The agency using the algorithm could then conduct their own investigations to confirm the algorithm’s findings.

If this algorithm is ever fully developed, however, Kearns believes that it would take a significant amount of time for it to be implemented, particularly because of the ongoing debates on privacy and its place in the United States. Kearns believes that if the nation is to ever see an algorithm that might give a guarantee of private security, it would require a profound change in thought.

“It feels right now that on the topic of the NSA metadata, that there is this polarizing dialogue where either you are a privacy advocate and all of this metadata is obscenely inappropriate to even have, and then there is this other camp that believes that it’s terrorism, so all bets are off ... as long as the debate is dominated by these two viewpoints, we are not going to get anywhere,” Kearns said.

For now, Kearns believes that more research is needed to strengthen the algorithm and make it more useful as a counterterrorism tool. However, this research is one step toward a guarantee of privacy for a nation’s citizens.

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