{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/attack-graph-obfuscation","title":"Attack Graph Obfuscation","arxiv_id":"1903.02601","date":"2019-03-06","proceeding":null,"authors":["Rami Puzis","Hadar Polad","Bracha Shapira"],"abstract":"Before executing an attack, adversaries usually explore the victim's network\nin an attempt to infer the network topology and identify vulnerabilities in the\nvictim's servers and personal computers. Falsifying the information collected\nby the adversary post penetration may significantly slower lateral movement and\nincrease the amount of noise generated within the victim's network. We\ninvestigate the effect of fake vulnerabilities within a real enterprise network\non the attacker performance. We use the attack graphs to model the path of an\nattacker making its way towards a target in a given network. We use\ncombinatorial optimization in order to find the optimal assignments of fake\nvulnerabilities. We demonstrate the feasibility of our deception-based defense\nby presenting results of experiments with a large scale real network. We show\nthat adding fake vulnerabilities forces the adversary to invest a significant\namount of effort, in terms of time and exploitability cost.","url_abs":"http://arxiv.org/abs/1903.02601v1","url_pdf":"http://arxiv.org/pdf/1903.02601v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"attack-graph-obfuscation","repo_url":"https://github.com/impredicative/irc-rss-feed-bot","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"AGPL-3.0"}}],"tasks":[{"task_slug":"combinatorial-optimization","task_name":"Combinatorial Optimization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}