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🌐 Entity
Adversarial machine learning
Research field that lies at the intersection of machine learning and computer security
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📌 Topics
- Cybersecurity (1)
- Artificial Intelligence (1)
- Data Integrity (1)
🏷️ Keywords
Neural networks (1) · Data poisoning (1) · Acoustic classification (1) · Machine learning security (1) · Cryptographic verification (1) · Backdoor attacks (1) · Data provenance (1) · Attack surface (1)
📖 Key Information
Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks.
Machine learning techniques are mostly designed to work on specific problem sets, under the assumption that the training and test data are generated from the same statistical distribution (IID). However, this assumption is often dangerously violated in practical high-stake applications, where users may intentionally supply fabricated data that violates the statistical assumption.
📰 Related News (1)
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🇺🇸 Poisoned Acoustics
arXiv:2602.22258v1 Announce Type: cross Abstract: Training-data poisoning attacks can induce targeted, undetectable failure in deep neural networks b...
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