Visible to the public Deception Maze: A Stackelberg Game-Theoretic Defense Mechanism for Intranet Threats

TitleDeception Maze: A Stackelberg Game-Theoretic Defense Mechanism for Intranet Threats
Publication TypeConference Paper
Year of Publication2021
AuthorsLiu, Jieling, Wang, Zhiliang, Yang, Jiahai, Wang, Bo, He, Lin, Song, Guanglei, Liu, Xinran
Conference NameICC 2021 - IEEE International Conference on Communications
Keywordsadvanced persistent threat, Computational modeling, Conferences, Data Breach, Deception Technology, game theoretic security, game theory, Games, genetic algorithm, Human Behavior, human factors, Metrics, Organizations, Predictive Metrics, pubcrawl, Resiliency, Resource management, Scalability, simulation
Abstract

The intranets in modern organizations are facing severe data breaches and critical resource misuses. By reusing user credentials from compromised systems, Advanced Persistent Threat (APT) attackers can move laterally within the internal network. A promising new approach called deception technology makes the network administrator (i.e., defender) able to deploy decoys to deceive the attacker in the intranet and trap him into a honeypot. Then the defender ought to reasonably allocate decoys to potentially insecure hosts. Unfortunately, existing APT-related defense resource allocation models are infeasible because of the neglect of many realistic factors.In this paper, we make the decoy deployment strategy feasible by proposing a game-theoretic model called the APT Deception Game to describe interactions between the defender and the attacker. More specifically, we decompose the decoy deployment problem into two subproblems and make the problem solvable. Considering the best response of the attacker who is aware of the defender's deployment strategy, we provide an elitist reservation genetic algorithm to solve this game. Simulation results demonstrate the effectiveness of our deployment strategy compared with other heuristic strategies.

DOI10.1109/ICC42927.2021.9500765
Citation Keyliu_deception_2021