The dynamic behavior of a data dissemination protocol for network programming at scale
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Bluetooth worm propagation: mobility pattern matters!
ASIACCS '07 Proceedings of the 2nd ACM symposium on Information, computer and communications security
Dynamic Behavior of SIS Epidemic Model with Feedback on Regular Lattic
IAS '09 Proceedings of the 2009 Fifth International Conference on Information Assurance and Security - Volume 02
QoS supporting and optimal energy allocation for a cluster based wireless sensor network
Computer Communications
Qualitative behavior of SIS epidemic model on time scales
ASM'10 Proceedings of the 4th international conference on Applied mathematics, simulation, modelling
Epidemic data survivability in unattended wireless sensor networks
Proceedings of the fourth ACM conference on Wireless network security
Epidemic spread in mobile Ad Hoc networks: determining the tipping point
NETWORKING'11 Proceedings of the 10th international IFIP TC 6 conference on Networking - Volume Part I
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In this paper, a modified SIS epidemic model is proposed to study the dynamics of virus spread in wireless sensor networks. The sensor nodes are attacked by viruses and initially only a small number of nodes are infected. The virus spreads itself to its neighbour nodes by piggybacking on normal data via regular communications. The infected neighbour nodes repeat the process to their respective neighbour nodes. Each sensor node is installed with an antivirus program, which can be periodically refreshed to recover the infective nodes to the susceptible group. Some explicit solutions are derived, which can capture both the spatial and temporal dynamics of the virus spread process. An adjustable virus spread control scheme is developed to effectively restrain the virus outbreak and avoid the network failure. Numerical results and simulations are provided for validation. The proposed model and analysis method can be applied to different types of networks such as wireless networks, computer networks, biomedical networks and social networks.