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After surveying all-too-possible low level attacks on critical systems, we will introduce an alternative open source solution to peace-of-mind cryptography and private computing.

By using programmable logic chips, called Field Programmable Gate Arrays, this device is more open source than any common personal computing system to date.

Reinforcement learning has produced game-changing AI's that top human level performance in the game of Go and a myriad of hacked retro Atari games (e.g., Pong).

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Less well appreciated, however, is that machine learning can be susceptible to attack by, ironically, other machine learning models.

In this talk, we demonstrate an AI agent trained through reinforcement learning to modify malware to evade machine learning malware detection.

No math or machine learning background is required; fundamental understanding of malware and Windows PE files is a welcome; and previous experience hacking Atari Pong is a plus.

Hyrum Anderson Hyrum Anderson is technical director of data scientist at Endgame, where he leads research on detecting adversaries and their tools using machine learning.

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Sean Kanuck (1, 2) Konstantinos Karagiannis Garry Kasparov Matt Knight William Knowles Artem Kondratenko Itzik Kotler Amit Klein L Logan Lamb Rep.