2019/01/06 by Saeed Valizadeh, Marten van Dijk, Valizadeh, Saeed +1 · 1 citation
Computer Science · #Advanced Malware Detection Techniques #Computer Science and Game Theory (cs.GT) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Information and Cyber Security #Network Security and Intrusion Detection
paper · pdf · doi:10.48550/arxiv.1901.01598
openalex publication_date 2019/01/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We provide a general methodology for analyzing defender-attacker based "games" in which we model such games as Markov models and introduce a capacity region to analyze how defensive and adversarial strategies impact security. Such a framework allows us to analyze under what kind of conditions we can prove statements (about an attack objective k) of the form "if the attacker has a time budget Tbud, then the probability that the attacker can reach an attack objective ≥ k is at most poly(Tbud)negl(k)". We are interested in such rigorous cryptographic security guarantees (that describe worst-case guarantees) as these shed light on the requirements of a defender's strategy for preventing more and more the progress of an attack, in terms of the "learning rate" of a defender's strategy. We explain the damage an attacker can achieve by a "containment parameter" describing the maximally reached attack objective within a specific time window.