Evolutionary Proactive P2P Worm: Propagation Modeling and Simulation

Stability Analysis of P2P Worm Propagation Model with Dynamic Quarantine Defense

“…Yejiang Zhang et al [25] proposed the model of proactive P2P worm based on unstructured peer to peer network. They drew two important conclusions, on the one hand, proactive P2P worm propagations are difficult to suspend owing to a rapid propagation speed; on the other hand, worms propagate faster once starting from large-degree node than small-degree node if treating the P2P network as a graph.…”

Modeling and Analysis of the Proactive Worm in Unstructured Peer-to-Peer Network

“…Zhang et al modeled P2P network topology as a power law undirected graph. They adopted discretetime to conduct recursive analysis and deterministic approximation to describe propagation of proactive P2P worms, and carried out extensive simulation studies [8] .…”

Propagation of Active Worms in P2P Networks: Modeling and Analysis

“…A great deal of research has been done on active worms' propagation model and defensive measure within recent years. For instance, Chen et al developed an active worm propagation model on the basis of discrete time [1]; Yu et al analyzed the propagation strategy and propagation process of P2P worms based on simple epidemic model applied to static network topology [2]; they also compared P2P worm propagation performance in four different attack strategies, indicating P2P worms based on hit-list scanning strategy best attack-efficient [3]; A method of building secure P2P networks using benign worms against malicious worms was introduced by Jia et al [4]; Wang et al presented a propagation model of active P2P worms under Chord networks [5]; Moreover, Ravikumar et al modeled the spread of malware in decentralized, Gnutella type of peer-to-peer networks [6]; And propagation procedure of active worm in P2P networks based on topology scanning strategy using of logic matrix was addressed by Fan [7] [8]; Additionally Zhang et al completed a static model on active worms within unstructured P2P system [9]; Besides a dynamic quarantine protocol towards defending active worms in P2P networks was designed by Yang et al quarantining the suspicious host, and they developed a corresponding mathematical model of PWPQ to prove the effectiveness of this method [10]; Chen et al brought forward a repairand-patch approach to quarantine malicious worms quickly in unstructured P2P networks [11]; In addition, Feng et al [12] and Li et al [13] respectively addressed two propagation models of active worms with the reference to degree difference of nodes under unstructured P2P networks; Suto et al proposed a method constructing network matching bimodal-degree distribution [14], thus being naturally robust against both attack and failure, and they obtained simulation results proving it eligible for higher resilience; A membership function of trusted set was established by Zhou et al according to the trusted level in the P2P trust model and maximum membership principle [15], the simulation results showed that the method was strong applicability in the event that the granularity of trusted level was great; Guo et al proposed a peer classification method based on fuzzy clustering [16], and proved their method could effectively avoid false recommendation, and enhanced the accuracy of trust evaluation in P2P networks; Meng et al came up with a hierarchical clustering P2P network model based on user interest in [17], and the simulation results showed this method could form cluster more rapidly and gain the appropriate resources faster than traditional algorithm.…”