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Performance Analysis of Cyber Deception Using Probabilistic Models

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abstract
With the recent development of cyber-crime and cyber-warefare, new techniques for thwarting cyber attackers are required. Deception is the a mechanism that at- tempts to distort or misled an adversary. It is a proven tactic leveraged in traditional warfare with a long history of noted successes. While deception has seen great success in traditional warfare, it has seen little use within the cyber security realm. Further- more, there is very little demonstrated modeling of such defenses in terms of attackers success. This thesis establishes a novel urn-modeling technique for providing the prob- ability of success for an attacker in two different network deception defenses, network address shuffling and honeypots. This work goes on to analyze these models in two scenarios, gaining a foothold and minimum to win, providing insight into the effect both defenses can have under various environments. Finally, this thesis performs an empirical analysis of network address shuffling to provide a cost-benefit analysis regarding attack success and the effect on legitimate network users.
subject
deception
honeypots
network address shuffling
networks
security
urn models
contributor
Crouse, Michael (author)
Fulp, Errin W (committee chair)
John, David J (committee member)
Canas, Daniel A (committee member)
date
2012-06-12T08:35:48Z (accessioned)
2012-12-12T09:30:06Z (available)
2012 (issued)
degree
Computer Science (discipline)
embargo
2012-12-12 (terms)
identifier
http://hdl.handle.net/10339/37258 (uri)
language
en (iso)
publisher
Wake Forest University
title
Performance Analysis of Cyber Deception Using Probabilistic Models
type
Thesis

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