Composite Backdoor Attack for Deep Neural Network by Mixing Existing Benign Features

Research article (Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications Security, 2020) · cited 198× · AI/ML
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Composite Backdoor Attack for Deep Neural Network by Mixing Existing Benign Features

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Composite Backdoor Attack for Deep Neural Network by Mixing Existing Benign Features is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Composite Backdoor Attack for Deep Neural Network by Mixing Existing Benign Features. Retrieved May 24, 2026, from https://4ort.xyz/entity/composite-backdoor-attack-for-deep-neural-network-by-mixing-existing-benign-features
MLA “Composite Backdoor Attack for Deep Neural Network by Mixing Existing Benign Features.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/composite-backdoor-attack-for-deep-neural-network-by-mixing-existing-benign-features.
BibTeX @misc{4ortxyz_composite-backdoor-attack-for-deep-neural-network-by-mixing-existing-benign-features_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Composite Backdoor Attack for Deep Neural Network by Mixing Existing Benign Features}}, year = {2026}, url = {https://4ort.xyz/entity/composite-backdoor-attack-for-deep-neural-network-by-mixing-existing-benign-features}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Composite Backdoor Attack for Deep Neural Network by Mixing Existing Benign Features — https://4ort.xyz/entity/composite-backdoor-attack-for-deep-neural-network-by-mixing-existing-benign-features (retrieved 2026-05-24)

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