AISec '22: 15th ACM Workshop on Artificial Intelligence and Security

Ambra Demontis, Xinyun Chen, Florian Tramèr
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引用次数: 0

Abstract

Recent years have seen a dramatic increase in applications of Artificial Intelligence (AI), Machine Learning (ML), and data mining to security and privacy problems. The analytic tools and intelligent behavior provided by these techniques make AI and ML increasingly important for autonomous real-time analysis and decision making in domains with a wealth of data or that require quick reactions to constantly changing situations. The use of learning methods in security-sensitive domains, in which adversaries may attempt to mislead or evade intelligent machines, creates new frontiers for security research. The recent widespread adoption of "deep learning" techniques, whose security properties are difficult to reason about directly, has only added to the importance of this research. In addition, data mining and machine learning techniques create a wealth of privacy issues, due to the abundance and accessibility of data. The AISec workshop provides a venue for presenting and discussing new developments in the intersection of security and privacy with AI and machine learning.
第15届美国计算机学会人工智能与安全研讨会
近年来,人工智能(AI)、机器学习(ML)和数据挖掘在安全和隐私问题上的应用急剧增加。这些技术提供的分析工具和智能行为使得人工智能和机器学习在具有丰富数据或需要对不断变化的情况做出快速反应的领域中,对于自主实时分析和决策越来越重要。在安全敏感领域使用学习方法,在这些领域,对手可能试图误导或逃避智能机器,为安全研究创造了新的领域。最近广泛采用的“深度学习”技术,其安全性很难直接推理,只会增加这项研究的重要性。此外,由于数据的丰富性和可访问性,数据挖掘和机器学习技术产生了大量的隐私问题。AISec研讨会提供了一个展示和讨论安全和隐私与人工智能和机器学习交叉领域的新发展的场所。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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