conference-paper

10th International Workshop on Artificial Intelligence and Security (AISec 2017)

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Abstract

Artificial Intelligence (AI) and Machine Learning (ML) provide a set of useful analytic and decision-making techniques that are being leveraged by an ever-growing community of practitioners, including many whose applications have security-sensitive elements. However, while security researchers often utilize such techniques to address problems and AI/ML researchers develop techniques for Big Data analytics applications, neither community devotes much attention to the other. Within security research, AI/ML components are usually regarded as black-box solvers. Conversely, the learning community seldom considers the security/privacy implications entailed in the application of their algorithms when they are designing them. While these two communities generally focus on different directions, where these two fields do meet, interesting problems appear. Researchers working in this intersection have raised many novel questions for both communities and created a new branch of research known as secure learning. The AISec workshop has become the primary venue for this unique fusion of research.

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Publication details

DOI
10.1145/3133956.3137048
OpenAlex
W4250268591
Document type
conference-paper
Language
EN
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