| 期刊全称 | Artificial Intelligence Tools for Cyber Attribution | | 影响因子2023 | Eric Nunes,Paulo Shakarian,Andrew Ruef | | 视频video | | | 学科分类 | SpringerBriefs in Computer Science | | 图书封面 |  | | 影响因子 | .This SpringerBrief discusses how to develop intelligent systems for cyber attribution regarding cyber-attacks. Specifically, the authors review the multiple facets of the cyber attribution problem that make it difficult for “out-of-the-box” artificial intelligence and machine learning techniques to handle... Attributing a cyber-operation through the use of multiple pieces of technical evidence (i.e., malware reverse-engineering and source tracking) and conventional intelligence sources (i.e., human or signals intelligence) is a difficult problem not only due to the effort required to obtain evidence, but the ease with which an adversary can plant false evidence...This SpringerBrief not only lays out the theoretical foundations for how to handle the unique aspects of cyber attribution – and how to update models used for this purpose – but it also describes a series of empirical results, as well as compares results of specially-designed frameworks for cyber attribution to standard machine learning approaches... Cyber attribution is not only a challenging problem, but there are also problems in performing such research, particularly in obtaining relevant data. This SpringerBrief desc | | Pindex | Book 2018 |
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发表于 2025-3-21 18:31:31
