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Evasion Attacks against Machine Learning at Test Time
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“They demonstrated that DBA is substantially more persistent and stealthy on diverse datasets such as finance and image data.”
From Vulnerabilities in federated learning (2021) · cites this paper as [44]
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“However, only a few works [44] investigate the poisoning attacks in a distributed environment where multiple malicious clients with the same attack strive to include poisoned training samples into the training procedures.”
From Vulnerabilities in federated learning (2021) · cites this paper as [44]
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Galli, D., Venturi, A., Stabili, D., Andreolini, M., & Marchetti, M. (2025) · IEEE International Symposium on Network Computing and Applications (NCA) · doi:10.1109/nca67271.2025.00043 · Cited by 3
Chain-of-Thought Prompt Optimization via Adversarial Learning
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Yang, X. H., & Zhu, J. (2023) · Springer eBooks · doi:10.1007/978-3-031-43567-6_13 · Cited by 3
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Yang, Z., Cao, J., Liu, Z., Zhang, X., Sun, K., & Li, Q. L. (2022) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2022.3154244 · Cited by 3
Metadata
- Authors
- Biggio, B., Corona, I., Maiorca, D., Nelson, B., Šrndić, N., Laskov, P., Giacinto, G., & Roli, F.
- Affiliations
- University of Cagliari (IT)
- University of Potsdam (DE)
- University of Tübingen (DE)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2013
- Pages
- 387-402
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W3103836116
- Cited by
- 890
- References
- 13
- Citations by year
- 2026: 35 · 2025: 103 · 2024: 131 · 2023: 123 · 2022: 126 · 2021: 95 · 2020: 98 · 2019: 98 · 2018: 37 · 2017: 26 · 2016: 7 · 2015: 5 · 2014: 4 · 2013: 1
- FWCI
- 3.66
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- UNICA IRIS Institutional Research Information System (University of Cagliari) (submittedVersion)
- CINECA IRIS Institutial Research Information System (University of Genoa) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Physical Sciences › Computer Science › Hardware and Architecture › Security and Verification in Computing
- Physical Sciences › Computer Science › Software › Advanced Malware Detection Techniques
- Keywords
- evasion attacks, adversarial learning, gradient-based attacks, malware detection, PDF documents, countermeasures
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