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Seminar: Adversarial Machine Learning

This seminar is concerned with different aspects of adversarial machine learning. Next to the use of machine learning for security, also the security of machine learning algorithms is essential in practice. For a long time, machine learning has not considered worst-case scenarios and corner cases as those exploited by an adversarial nowadays. The module introduces students to the recently extremely active field of attacks against machine learning and teaches them to work up results from recent research. To this end, the students will read up on a sub-field, prepare a seminar report, and present their work at the end of the term to their colleagues. Topics include but are not limited to adversarial examples, model stealing, membership inferences, poisoning attacks, and defenses against such threats. More information can be found at https://intellisec.de/teaching/aml
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Description

This seminar is concerned with different aspects of adversarial machine learning. Next to the use of machine learning for security, also the security of machine learning algorithms is essential in practice. For a long time, machine learning has not considered worst-case scenarios and corner cases as those exploited by an adversarial nowadays.

The module introduces students to the recently extremely active field of attacks against machine learning and teaches them to work up results from recent research. To this end, the students will read up on a sub-field, prepare a seminar report, and present their work at the end of the term to their colleagues.

Topics include but are not limited to adversarial examples, model stealing, membership inferences, poisoning attacks, and defenses against such threats.


More information can be found at https://intellisec.de/teaching/aml

General

Language
German
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Availability

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1. Sep 2021, 18:00 - 1. Mar 2022, 17:00
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Registration Period
Until 8. Nov 2021, 23:55
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4. Nov 2021
Period of Event
19. Oct 2021 - 11. Feb 2022

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2147168
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