How web data saves lives, identifies threats, and brings criminals to justice

The team will remember February 13th 2017 primarily because of the opportunity to present at i-HLS Big Data alongside Fortune 500 leaders including IBM, SAP, and Dell. Over 500 participants convened to learn how homeland security and law enforcement agencies are using big data to serve and protect. Of particular interest was the role of dark web monitoring data in open source threat intelligence (OSINT).
On a more somber note, February 13th also marked the continuing trial of Stephen Allwine who is accused of murdering his wife Amy in November of 2016. Although this particular case is hardly the first time a digital trail was used to collect hard evidence, it has received extensive media coverage especially as it involved anonymized Darknet data leaked from TOR networks. Of course, no account of a murder conspiracy involving a digitally contracted assassination hit would be complete without a documented Reddit thread. The unraveling of events is so bizarre it sounds like a discarded plot idea from an episode of CSI Cyber.

The case presents a disturbing example of the clues criminals and terrorists leave behind as a digital trail. However, it also suggests how such threats could be identified and even prevented given the right data and means to process it in time.

Last week, SC Magazine UK reported just how law enforcement agencies could approach the challenge. Working at the University of Technology in Troyes, France, researchers Omar Jaafor and Babiga Birregah collected Tweets and web data queried from the API.
Currently such techniques are limited to research and classified research projects, but the technology is gradually being adopted by a variety of government agencies and commercial enterprises.


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