Code red worm propagation modeling and analysis
Proceedings of the 9th ACM conference on Computer and communications security
WORM vs. WORM: preliminary study of an active counter-attack mechanism
Proceedings of the 2004 ACM workshop on Rapid malcode
The Art of Computer Virus Research and Defense
The Art of Computer Virus Research and Defense
On the effectiveness of automatic patching
Proceedings of the 2005 ACM workshop on Rapid malcode
Performance modeling of epidemic routing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Proceedings of the second ACM workshop on Challenged networks
A family of encounter-based broadcast protocols for mobile ad-hoc networks
NGI'04 Proceedings of the First international conference on Wireless Systems and Mobility in Next Generation Internet
Models and analysis of active worm defense
MMM-ACNS'05 Proceedings of the Third international conference on Mathematical Methods, Models, and Architectures for Computer Network Security
Maximum damage malware attack in mobile wireless networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
Influence of removable devices on computer worms: Dynamic analysis and control strategies
Computers & Mathematics with Applications
Containment of misinformation spread in online social networks
Proceedings of the 3rd Annual ACM Web Science Conference
Maximum damage malware attack in mobile wireless networks
IEEE/ACM Transactions on Networking (TON)
Analysis of misinformation containment in online social networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
A cutting-plane algorithm for solving a weighted influence interdiction problem
Computational Optimization and Applications
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An encounter-based network is a frequently disconnected wireless ad hoc network requiring immediate neighbors to store and forward aggregated data for information disseminations. Using traditional approaches such as gateways or firewalls to deter worm propagation in encounter-based networks is inappropriate. We propose a worm interaction approach that relies upon automated beneficial worm generation to alleviate problems of worm propagations in such networks. To understand the dynamics of worm interactions and their performance, we mathematically model worm interactions based on major worm interaction factors, including worm interaction types, network characteristics, and node characteristics using ordinary differential equations and analyze their effects on our proposed metrics. We validate our proposed model using extensive synthetic and trace-driven simulations. We find that all worm interaction factors significantly affect the pattern of worm propagations. For example, immunization linearly decreases the infection of susceptible nodes, while on-off behavior only impacts the duration of infection. Using realistic mobile network measurements, we find that encounters are ''bursty'', multi-group, and non-uniform. The trends from the trace-driven simulations are consistent with the model, in general. Immunization and timely deployment seem to be most effective in countering worm attacks in such scenarios, while cooperation may help in a specific case. These findings provide insight that we hope would aid in the development of counter-worm protocols in future encounter-based networks.