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Suzanne Schwartz (1, 2) Nathan Seidle Shaggy Haoqi Shan Mickey Shkatov Eden Shochat Marina Simakov skud Sky Dimitry Snezhkov Mikhail Sosonkin John Sotos S0ups space B0x Jason Staggs Gerald Steere Jayson E.Street Suggy Matt Suiche T TBA Evan Teitelman Richard Thieme Chris Thompson trixr4skids Orange Tsai Jeff "r3plicant" Tully MD Philip Tully V Ilja van Sprundel [email protected] W Kit Walsh Patrick Wardle (1, 2) Waz Wiseacre Matt Wixey Beau Woods X Xlogic X Y Luke Young Jian Yuan Zhang Yunhai Z Zardus Sarah Zatko Zenofex zerosum0x0 Min (Spark) Zheng Sunday at in Track 4 20 minutes | Demo, Tool Modern computing platforms offer more freedom than ever before.

He received his Ph D in Electrical Engineering (signal and image processing machine learning) from the University of Washington and BS/MS degrees from Brigham Young University.No blobs, no hidden firmware features, and no secret closed source processors.This concept isn't "unhacakable", rather we believe it to be the most fixable; this is what users and hackers should ultimately be fighting for.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.

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