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Artificial Intelligence Tools for Cyber Attribution (SpringerBriefs in Computer Science)

Amazon.com Price:  $42.27 (as of 01/05/2019 13:38 PST- Details)

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Description

This SpringerBrief discusses tips on how to develop intelligent systems for cyber attribution regarding cyber-attacks. Specifically, the authors review the more than one facets of the cyber attribution problem that make it difficult for “out-of-the-box” artificial intelligence and machine learning techniques to care for.

 Attributing a cyber-operation through using more than one 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 because of 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 tips on how to care for the unique aspects of cyber attribution – and tips on how to update models used for this purpose – but it also describes a series of empirical results, in addition to compares results of specially-designed frameworks for cyber attribution to standard machine learning approaches.

 Cyber attribution is not just a challenging problem, but there are also problems in performing such research, particularly in obtaining relevant data. This SpringerBrief describes tips on how to use capture-the-flag for such research, and describes issues from organizing such data to running your own capture-the-flag specifically designed for cyber attribution. Datasets and software are also to be had at the companion web page.

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