| 期刊全称 | Anomaly Detection as a Service | | 期刊简称 | Challenges, Advances | | 影响因子2023 | Danfeng Daphne Yao,Xiaokui Shu,Salvatore J. Stolfo | | 视频video | | | 学科分类 | Synthesis Lectures on Information Security, Privacy, and Trust | | 图书封面 |  | | 影响因子 | .Anomaly detection has been a long-standing security approach with versatile applications, ranging from securing server programs in critical environments, to detecting insider threats in enterprises, to anti-abuse detection for online social networks. Despite the seemingly diverse application domains, anomaly detection solutions share similar technical challenges, such as how to accurately recognize various normal patterns, how to reduce false alarms, how to adapt to concept drifts, and how to minimize performance impact. They also share similar detection approaches and evaluation methods, such as feature extraction, dimension reduction, and experimental evaluation...The main purpose of this book is to help advance the real-world adoption and deployment anomaly detection technologies, by systematizing the body of existing knowledge on anomaly detection. This book is focused on data-driven anomaly detection for software, systems, and networks against advanced exploits and attacks, but also touches on a number of applications, including fraud detection and insider threats. We explain the key technical components in anomaly detection workflows, give in-depth description of the state-o | | Pindex | Book 2018 |
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发表于 2025-3-21 16:13:51
