EAN: 9783319737874

SPRINGERBRIEFS IN COMPUTER SCIENCE ARTIFICIAL...

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 describes 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 available on the companion website.

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