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Monday, August 12 • 3:00pm - 4:30pm
IPE 2 : Adaptive Adversaries: Building Systems to Fight Fraud and Cyber Intruders - Ari Gesher, Palantir

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Statistical machine learning / knowledge discovery techniques tend to fail when faced with an adaptive adversary attempting to evade detection in the data. Humans do an excellent job of correctly spotting adaptive adversaries given a good way to digest the data. On the other hand, humans are glacially slow and error-prone when it comes to moving through very large volumes of data, a task best left to the machines. Fighting complex fraud and cyber-security threats requires a symbiosis between the computers and teams of human analysts. The computers use algorithmic analysis, heuristics, and/or statistical characterization to nd interesting simple patterns in the data. These candidate events are then queued for in-depth human analysis in rich, expressive, interactive analysis environments. In this talk, well take a look at case studies of three different systems, using a partnership of automation and human analysis on large scale data to nd the clandestine human behavior that these datasets hold, including a discussion of the backend systems architecture and a demo of the interactive analysis environment. The backend systems architecture is a mix of open source technologies, like Cassandra, Lucene, and Hadoop, and some new components that bind them all together. The interactive analysis environment allows seamless pivoting between semantic, geospatial, and temporal analysis with a powerful GUI interface thats usable by non-data scientists. The systems are real systems currently in use by commercial banks, pharmaceutical companies, and governments.

Monday August 12, 2013 3:00pm - 4:30pm CDT

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