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Recent Advances in Computational Intelligence in Defense and Security Read chapter Read first chapter

2016 | OriginalPaper | Chapter

NNCS: Randomization and Informed Search for Novel Naval Cyber Strategies

Authors : Stuart H. Rubin, Thouraya Bouabana-Tebibel

Published in: Recent Advances in Computational Intelligence in Defense and Security

Publisher: Springer International Publishing

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Abstract

Software security is increasingly a concern as cyber-attacks become more frequent and sophisticated. This chapter presents an approach to counter this trend and make software more resistant through redundancy and diversity. The approach, termed Novel Naval Cyber Strategies (NNCS), addresses how to immunize component-based software. The software engineer programs defining component rule bases using a schema-based Very High Level Language (VHLL). Chance and ordered transformation are dynamically balanced in the definition of diverse components. The system of systems is shown to be relatively immune to cyber-attacks; and, as a byproduct, yield this capability for effective component generalization. This methodology offers exponential increases in cyber security; whereas, conventional approaches can do no better than linear. A sample battle management application—including rule randomization—is provided.

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previous chapter A Granular Intrusion Detection System Using Rough Cognitive Networks
next chapter Semi-Supervised Classification System for the Detection of Advanced Persistent Threats
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Metadata
Title
NNCS: Randomization and Informed Search for Novel Naval Cyber Strategies
Authors
Stuart H. Rubin
Thouraya Bouabana-Tebibel
Copyright Year
2016
Book
Recent Advances in Computational Intelligence in Defense and Security

Print ISBN: 978-3-319-26448-6

Electronic ISBN: 978-3-319-26450-9

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-26450-9_8

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