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Dataset Security For Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses PDF

37 Pages·2021·English
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by ['sdasd']| 2021| 37 pages| English

About Dataset Security For Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses

This document summarizes and categorizes different types of dataset security vulnerabilities and exploits for machine learning, including data poisoning and backdoor attacks. It discusses training-only attacks that manipulate training data without affecting test inputs, as well as attacks that target both training and testing phases by embedding an exploit during training that is triggered during testing. The document also reviews defenses against dataset tampering, including methods for detecting poisoning and training approaches that are robust to poisoning. It aims to systematically analyze this problem by providing a taxonomy of different attack strategies and discussing open challenges.

Detailed Information

Author:['sdasd']
Publication Year:2021
Pages:37
Language:English
Format:PDF
Price:FREE
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