ENGLISH

Artificial Intelligence Tools for Cyber Attribution

Book information

Publisher
Springer International Publishing
Year
2018
ISBN
978-3-319-73787-4, 978-3-319-73788-1
Language
english
Format
PDF
Filesize
5 MB (5572685 bytes)
Series
SpringerBriefs in Computer Science
Edition
1
Pages
VIII, 91\97
Time added
2018-03-04 00:00:30

Description

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. Front Matter ....Pages i-viii Introduction (Eric Nunes, Paulo Shakarian, Gerardo I. Simari, Andrew Ruef)....Pages 1-3 Baseline Cyber Attribution Models (Eric Nunes, Paulo Shakarian, Gerardo I. Simari, Andrew Ruef)....Pages 5-16 Argumentation-Based Cyber Attribution: The DeLP3E Model (Eric Nunes, Paulo Shakarian, Gerardo I. Simari, Andrew Ruef)....Pages 17-45 Belief Revision in DeLP3E (Eric Nunes, Paulo Shakarian, Gerardo I. Simari, Andrew Ruef)....Pages 47-74 Applying Argumentation Models for Cyber Attribution (Eric Nunes, Paulo Shakarian, Gerardo I. Simari, Andrew Ruef)....Pages 75-84 Enhanced Data Collection for Cyber Attribution (Eric Nunes, Paulo Shakarian, Gerardo I. Simari, Andrew Ruef)....Pages 85-90 Conclusion (Eric Nunes, Paulo Shakarian, Gerardo I. Simari, Andrew Ruef)....Pages 91-91

Similar books