An introduction to adversarial attacks and defences

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• Yingzhen Li (University of Cambridge)
• Wednesday 08 November 2017, 17:00-18:30
• Cambridge University Engineering Department, CBL Seminar room BE4-38. For directions see http://learning.eng.cam.ac.uk/Public/Directions.

If you have a question about this talk, please contact Adrià Garriga Alonso.

AI safety is not limited to RL settings. For example, we can use machine learning algorithms to design spam filters, yet attackers can still “reverse-engineer” our defence to send us junk emails. Autonomous driving systems based on computer vision techniques are also vulnerable to attacks, for instance, attackers can carefully apply a sticker to a stop sign in order to fool the vision system of the car. In this talk I will briefly discuss the mathematical framework of these attack techniques (specifically on image classifiers) and defence techniques against them.

Slides available here: http://yingzhenli.net/home/pdf/attack_defence.pdf

This talk is part of the Engineering Safe AI series.

This talk is included in these lists:

• Cambridge University Engineering Department, CBL Seminar room BE4-38. For directions see http://learning.eng.cam.ac.uk/Public/Directions
• Cambridge talks
• Chris Davis' list
• Engineering Safe AI
• Trust & Technology Initiative - interesting events

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