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Adversarial Analytics 101

Robert Grossman (Open Data Group)
Hardcore Data Science Gramercy Suite
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Many analytic and data science problems are about trying to understand the data well enough to build a model with good predictive power, but there are also some analytic problems in which the effectiveness of this predictive model is undermined by an adversary. Adversaries tend to change their tactics and signatures to reduce the effectiveness of the opposing predictive model.

One type of adversarial analytics occurs when predictive models are used to defend a system. For example, the system may be a payments card processing system, the predictive model may be a fraud model, and the adversary may be a criminal engaged in credit card fraud. Another example of this type is provided by behavioral models that try to detect cyber intrusions and black hat hackers that try to evade these models.

Another type of adversarial analytics occurs when multiple predictive models are competing for resources. For example, the system may be an ad exchange, the predictive models may be models that predict how much revenue the ad will produce, and the adversary may be other predictive models bidding on the same or related ads. Another example of this type, are high momentum trading systems, in which cases the adversaries are usually other predictive models from competing firms.

In this talk, we give an introduction to adversarial analytics, giving examples from fraud, real time bidding systems and cybersecurity.

Photo of Robert Grossman

Robert Grossman

Open Data Group

Robert Grossman is the Founder and a Partner of Open Data Group, which specializes in building predictive models over big data. He is also a Senior Fellow at the Institute for Genomics and Systems Biology (IGSB) and Computation Institute (CI) at the University of Chicago and a Professor in the Biological Sciences Division. His areas of research include: big data, bioinformatics, and data intensive computing. He has led the development of new open source software tools for analyzing big data, cloud computing and high performance networking. Prior to starting Open Data Group, he founded Magnify, Inc. in 1996, which provides data mining solutions to the insurance industry. Grossman was Magnify’s CEO until 2001 and its Chairman until it was sold to ChoicePoint in 2005. He blogs occasionaly about big data, data science, and data engineering at


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