2016/03/14 by Phillip Lee, Lee, Phillip, Andrew L. Clark +7
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #FOS: Electrical engineering #Network Security and Intrusion Detection #Opportunistic and Delay-Tolerant Networks #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1603.04374
openalex publication_date 2016/03/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Malware propagation poses a growing threat to networked systems such as\ncomputer networks and cyber-physical systems. Current approaches to defending\nagainst malware propagation are based on patching or filtering susceptible\nnodes at a fixed rate. When the propagation dynamics are unknown or uncertain,\nhowever, the static rate that is chosen may be either insufficient to remove\nall viruses or too high, incurring additional performance cost. In this paper,\nwe formulate adaptive strategies for mitigating multiple malware epidemics when\nthe propagation rate is unknown, using patching and filtering-based defense\nmechanisms. In order to identify conditions for ensuring that all viruses are\nasymptotically removed, we show that the malware propagation, patching, and\nfiltering processes can be modeled as coupled passive dynamical systems. We\nprove that the patching rate required to remove all viruses is bounded above by\nthe passivity index of the coupled system, and formulate the problem of\nselecting the minimum-cost mitigation strategy. Our results are evaluated\nthrough numerical study.\n