Practical machine learning in infosecurity

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Authors: Anto Joseph and Clarence Chio

Machine learning (ML) is the future. The speaker will give an introduction to the topic with the Boolean classification problem and introduce classifiers, which are at the core of many of the most common ML systems. He will also provide a simple example of deploying security machine learning systems in production pipelines using Apache Spark. The speaker will talk about how such systems can be poisoned, misguided, and utterly broken if the architects and implementers are not careful.

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  • English

Anto Joseph
A security engineer at Intel. He has 5 years of corporate experience in developing and advocating security in mobile and web platforms. Machine learning is one of his key areas of interest. He has been a presenter and trainer at various security conferences including BH USA 2016, DEF CON 24, BruCon, HackInParis, HITB Amsterdam, NullCon, GroundZero, c0c0n, XorConf.

Clarence Chio
Graduated with a B.S. and M.S. in Computer Science from Stanford within four years, specializing in data mining and artificial intelligence. Currently works as a security researcher at Shape Security, building a product that protects high-valued web assets from automated attacks. Spoke on machine learning and security at DEFCON 24, GeekPwn, PHDays, BSides, Code Blue, SecTor, GrrCon, Hack in Paris, QCon, and DeepSec. A community speaker with Intel, and is also the founder and organizer of the Data Mining for Cyber Security meetup group, the largest gathering of security data scientists in the San Francisco Bay Area.

Anto Joseph and Clarence Chio Anto Joseph and Clarence Chio

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