第十届人工智能与安全国际研讨会(AISec 2017)

B. Biggio, D. Freeman, Brad Miller, Arunesh Sinha
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引用次数: 2

摘要

人工智能(AI)和机器学习(ML)提供了一套有用的分析和决策技术,这些技术正在被不断增长的从业者社区所利用,其中包括许多具有安全敏感元素的应用程序。然而,虽然安全研究人员经常利用这些技术来解决问题,人工智能/机器学习研究人员为大数据分析应用开发技术,但这两个社区都不太关注对方。在安全研究中,AI/ML组件通常被视为黑盒解决方案。相反,学习社区在设计算法时很少考虑其应用所涉及的安全/隐私问题。虽然这两个社区通常关注不同的方向,但在这两个领域相遇的地方,出现了有趣的问题。在这个交叉点工作的研究人员为这两个社区提出了许多新颖的问题,并创造了一个新的研究分支,即安全学习。AISec研讨会已成为这一独特研究融合的主要场所。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
10th International Workshop on Artificial Intelligence and Security (AISec 2017)
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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