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- W4308409904 abstract "As the practicality of Artificial Intelligence (AI) and Machine Learning (ML) based techniques grow, there is an ever increasing threat of adversarial attacks. There is a need to red team' this ecosystem to identify system vulnerabilities, potential threats, characterize properties that will enhance system robustness, and encourage the creation of effective defenses. A secondary need is to share this AI security threat intelligence between different stakeholders like, model developers, users, and AI/ML security professionals. In this paper, we create and describe a prototype system CTI4AI, to overcome the need to methodically identify and share AI/ML specific vulnerabilities and threat intelligence." @default.
- W4308409904 created "2022-11-11" @default.
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- W4308409904 date "2022-11-07" @default.
- W4308409904 modified "2023-10-01" @default.
- W4308409904 title "Poster CTI4AI" @default.
- W4308409904 cites W2194775991 @default.
- W4308409904 doi "https://doi.org/10.1145/3548606.3563525" @default.
- W4308409904 hasPublicationYear "2022" @default.
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