{"id":{"repo_id":"wfu","oai_identifier":"oai:wakespace.lib.wfu.edu:10339/37258"},"canonical_url":"https://search.dev.ndltd.org/etd/wfu/oai:wakespace.lib.wfu.edu:10339/37258","repository":{"repo_id":"wfu","name":"Wake Forest University","base_url":"https://wakespace.lib.wfu.edu/oai/request"},"display":{"title":"Performance Analysis of Cyber Deception Using Probabilistic Models","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Crouse, Michael"],"institution":"Wake Forest University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-27T22:01:27Z","subjects":["deception"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10339/37258","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Crouse, Michael"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2012-06-12T08:35:48Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2012-12-12T09:30:06Z"]},{"key":"dc:date.issued","label":"Date","values":["2012"]},{"key":"dc:publisher","label":"Institution","values":["Wake Forest University"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["deception"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10339/37258"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:title","label":"Title","values":["Performance Analysis of Cyber Deception Using Probabilistic Models"]}]}],"canonical_facts":{"dc:creator":["Crouse, Michael"],"dc:date.accessioned":["2012-06-12T08:35:48Z"],"dc:date.available":["2012-12-12T09:30:06Z"],"dc:date.issued":["2012"],"dc:description.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."],"dc:identifier.uri":["http://hdl.handle.net/10339/37258"],"dc:language.iso":["en"],"dc:publisher":["Wake Forest University"],"dc:subject":["deception"],"dc:title":["Performance Analysis of Cyber Deception Using Probabilistic Models"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T22:01:27Z"}