US plans massive data sweep
Little-known data-collection system could troll news, blogs, even e-mails. Will it go too far?
The US government is developing a massive computer system that can collect huge amounts of data and, by linking far-flung information from blogs and e-mail to government records and intelligence reports, search for patterns of terrorist activity.Skip to next paragraph
Subscribe Today to the Monitor
The system - parts of which are operational, parts of which are still under development - is already credited with helping to foil some plots. It is the federal government's latest attempt to use broad data-collection and powerful analysis in the fight against terrorism. But by delving deeply into the digital minutiae of American life, the program is also raising concerns that the government is intruding too deeply into citizens' privacy.
"We don't realize that, as we live our lives and make little choices, like buying groceries, buying on Amazon, Googling, we're leaving traces everywhere," says Lee Tien, a staff attorney with the Electronic Frontier Foundation. "We have an attitude that no one will connect all those dots. But these programs are about connecting those dots - analyzing and aggregating them - in a way that we haven't thought about. It's one of the underlying fundamental issues we have yet to come to grips with."
The core of this effort is a little-known system called Analysis, Dissemination, Visualization, Insight, and Semantic Enhancement (ADVISE). Only a few public documents mention it. ADVISE is a research and development program within the Department of Homeland Security (DHS), part of its three-year-old "Threat and Vulnerability, Testing and Assessment" portfolio. The TVTA received nearly $50 million in federal funding this year.
DHS officials are circumspect when talking about ADVISE. "I've heard of it," says Peter Sand, director of privacy technology. "I don't know the actual status right now. But if it's a system that's been discussed, then it's something we're involved in at some level."
A major part of ADVISE involves data-mining - or "dataveillance," as some call it. It means sifting through data to look for patterns. If a supermarket finds that customers who buy cider also tend to buy fresh-baked bread, it might group the two together. To prevent fraud, credit-card issuers use data-mining to look for patterns of suspicious activity.
What sets ADVISE apart is its scope. It would collect a vast array of corporate and public online information - from financial records to CNN news stories - and cross-reference it against US intelligence and law-enforcement records. The system would then store it as "entities" - linked data about people, places, things, organizations, and events, according to a report summarizing a 2004 DHS conference in Alexandria, Va. The storage requirements alone are huge - enough to retain information about 1 quadrillion entities, the report estimated. If each entity were a penny, they would collectively form a cube a half-mile high - roughly double the height of the Empire State Building.
But ADVISE and related DHS technologies aim to do much more, according to Joseph Kielman, manager of the TVTA portfolio. The key is not merely to identify terrorists, or sift for key words, but to identify critical patterns in data that illumine their motives and intentions, he wrote in a presentation at a November conference in Richland, Wash.
For example: Is a burst of Internet traffic between a few people the plotting of terrorists, or just bloggers arguing? ADVISE algorithms would try to determine that before flagging the data pattern for a human analyst's review.
At least a few pieces of ADVISE are already operational. Consider Starlight, which along with other "visualization" software tools can give human analysts a graphical view of data. Viewing data in this way could reveal patterns not obvious in text or number form. Understanding the relationships among people, organizations, places, and things - using social-behavior analysis and other techniques - is essential to going beyond mere data-mining to comprehensive "knowledge discovery in databases," Dr. Kielman wrote in his November report. He declined to be interviewed for this article.