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Adversarial Machine Learning: Lessons Learned and Future Challenges

智能感知与计算系列讲座
Lecture Series in Intelligent Perception and Computing 

    TITLE):Adversarial Machine Learning: Lessons Learned and Future Challenges

SPEAKER: Prof. Fabio Roli, University of Genova

(CHAIR)Prof. Zhaoxiang Zhang

    (TIME)Sept.29, 2022 (Thursday),15:00

    (VENUE) Tecent Meeting ID:211 672 287


报告摘要(ABSTRACT):

Machine-learning algorithms are widely used for cybersecurity applications, including spam, malware detection, biometric recognition. In these applications, the learning algorithm must face intelligent and adaptive attackers who can carefully manipulate data to purposely subvert the learning process. As machine learning algorithms have not been originally designed under such premises, they have been shown to be vulnerable to well-crafted attacks, including test-time evasion and training-time poisoning attacks (also known as adversarial examples). This talk aims to introduce the fundamental concepts of adversarial machine learning and discuss some of the future open challenges.


报告人简介(BIOGRAPHY):

Fabio Roli is Full Professor of Computer Engineering at the University of Genova, Italy. He is founding Director of the Pattern Recognition and Applications laboratory at the University of Cagliari (https://pralab.diee.unica.it/). He is partner of the company Pluribus One that he co-founded (https://www.pluribus-one.it). He has been doing research on the design of pattern recognition and machine learning systems for thirty years. He has been appointed Fellow of the IEEE, Fellow of the International Association for Pattern Recognition, Fellow of the Asia-Pacific Artificial Intelligence Association. He was a recipient of the Pierre Devijver Award for his contributions to statistical pattern recognition and 2020 “Pattern Recognition Medal” of the international journal Pattern Recognition.

 


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