Managing risk in high assurance systems by optimizing topological resources

Managing risk in high assurance systems by optimizing topological resources We explore strategies for manipulating the topology of a network to promote increased and pragmatic high assurance systems. Topology matters to network threats and security, and the relative distance between nodes can impact the rate of dispersion of viruses, as well as access times in denial of service, probing, and insider threat attacks. We suggest methods to separate threatening and threatened nodes with enough hops to reduce and degrade risks. This work provides network analysts with an option to include other measures such as risk assessments to the construction and management of high assurance systems. We consider a scaled down model to demonstrate the proof of concept using artificial data. Specifically, we explore the efficacy of ring networks and the structure that occurs on k‐hop networks when there are a prime number of nodes. We introduce techniques for the randomization of network topologies to manage real‐time risk and provide a dynamic means to improve network security by increasing technical debt to a potential attacker. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Software: Evolution and Process Wiley

Managing risk in high assurance systems by optimizing topological resources

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Copyright © 2018 John Wiley & Sons, Ltd.
ISSN
2047-7473
eISSN
2047-7481
D.O.I.
10.1002/smr.1887
Publisher site
See Article on Publisher Site

Abstract

We explore strategies for manipulating the topology of a network to promote increased and pragmatic high assurance systems. Topology matters to network threats and security, and the relative distance between nodes can impact the rate of dispersion of viruses, as well as access times in denial of service, probing, and insider threat attacks. We suggest methods to separate threatening and threatened nodes with enough hops to reduce and degrade risks. This work provides network analysts with an option to include other measures such as risk assessments to the construction and management of high assurance systems. We consider a scaled down model to demonstrate the proof of concept using artificial data. Specifically, we explore the efficacy of ring networks and the structure that occurs on k‐hop networks when there are a prime number of nodes. We introduce techniques for the randomization of network topologies to manage real‐time risk and provide a dynamic means to improve network security by increasing technical debt to a potential attacker.

Journal

Journal of Software: Evolution and ProcessWiley

Published: Jan 1, 2018

Keywords: ; ;

References

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