Combating Advanced Persistent Threats: Challenges and Solutions

• URL: http://arxiv.org/abs/2309.09498v2
• Date: Fri, 12 Apr 2024 06:10:43 GMT
• Title: Combating Advanced Persistent Threats: Challenges and Solutions
• Authors: Yuntao Wang, Han Liu, Zhendong Li, Zhou Su, Jiliang Li,
• Abstract summary: The rise of advanced persistent threats (APTs) has marked a significant cybersecurity challenge. Provenance graph-based kernel-level auditing has emerged as a promising approach to enhance visibility and traceability. This paper proposes an efficient and robust APT defense scheme leveraging provenance graphs, including a network-level distributed audit model for cost-effective lateral attack reconstruction.
• Score: 20.81151411772311
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The rise of advanced persistent threats (APTs) has marked a significant cybersecurity challenge, characterized by sophisticated orchestration, stealthy execution, extended persistence, and targeting valuable assets across diverse sectors. Provenance graph-based kernel-level auditing has emerged as a promising approach to enhance visibility and traceability within intricate network environments. However, it still faces challenges including reconstructing complex lateral attack chains, detecting dynamic evasion behaviors, and defending smart adversarial subgraphs. To bridge the research gap, this paper proposes an efficient and robust APT defense scheme leveraging provenance graphs, including a network-level distributed audit model for cost-effective lateral attack reconstruction, a trust-oriented APT evasion behavior detection strategy, and a hidden Markov model based adversarial subgraph defense approach. Through prototype implementation and extensive experiments, we validate the effectiveness of our system. Lastly, crucial open research directions are outlined in this emerging field.

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