In this paper, the spreading of malicious software over ad hoc networks, where legitimate nodes are prone to propagate the infections they receive from either an attacker or their already infected neighbors, is analyz...In this paper, the spreading of malicious software over ad hoc networks, where legitimate nodes are prone to propagate the infections they receive from either an attacker or their already infected neighbors, is analyzed. Considering the Susceptible-Infected-Susceptible （SIS） node infection paradigm we propose a probabilistic model, on the basis of the theory of closed queuing networks, that aims at describing the aggregated behavior of the system when attacked by malicious nodes. Because of its nature, the model is also able to deal more effectively with the stochastic behavior of attackers and the inherent probabilistic nature of the wireless environment. The proposed model is able to describe accurately the asymptotic behavior of malware-propagative large scale ad hoc networking environments. Using the Norton equivalent of the closed queuing network, we obtain analytical results for its steady state behavior, which in turn is used for identifying the critical parameters affecting the operation of the network. Finally, through modeling and simulation, some additional numerical results are obtained with respect to the behavior of the system when multiple attackers are present, and regarding the time-dependent evolution and impact of an attack.展开更多
基金Greek General Secretariat for Research and Technology of the Ministry of Development(PENED project under Grant No.03ED840).
文摘In this paper, the spreading of malicious software over ad hoc networks, where legitimate nodes are prone to propagate the infections they receive from either an attacker or their already infected neighbors, is analyzed. Considering the Susceptible-Infected-Susceptible （SIS） node infection paradigm we propose a probabilistic model, on the basis of the theory of closed queuing networks, that aims at describing the aggregated behavior of the system when attacked by malicious nodes. Because of its nature, the model is also able to deal more effectively with the stochastic behavior of attackers and the inherent probabilistic nature of the wireless environment. The proposed model is able to describe accurately the asymptotic behavior of malware-propagative large scale ad hoc networking environments. Using the Norton equivalent of the closed queuing network, we obtain analytical results for its steady state behavior, which in turn is used for identifying the critical parameters affecting the operation of the network. Finally, through modeling and simulation, some additional numerical results are obtained with respect to the behavior of the system when multiple attackers are present, and regarding the time-dependent evolution and impact of an attack.
