Network-Based Detection Method against Proactive P2P Worms Leveraging Application-Level Knowledge

Li, Zhitang; Zhang, Yejiang; Hu, Zhengbing; Lin, Haoming; Lu, Chuiwei

doi:10.1109/etcs.2009.661

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…With the development of the mobile network technology and the gradually mature of P2P network technology, the mobile P2P network combining with mobile computing and P2P technology is emerged [1]. Mobile P2P Network (Mobile Peer-to-Peer Network) is also called Mobile peer-to-peer Network, it is based on the Mobile wireless Network, the nodes in the Network is usually a Mobile phone, PDA and other Mobile devices, these devices have a certain particularity, such as small storage capacity, low processing power and limited Network bandwidth and limited battery energy, etc [2].…”

Section: Introductionmentioning

confidence: 99%

Data Flow Control Algorithm based on Feature Matching in Mobile P2P Network

Zhang¹,

Shen²

2013

JNW

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This paper proposes a characteristic matching based mobile P2P network data flow control algorithm, to detect the illegal data flow in the mobile P2P network, finally achieve the purpose of control the data flow. The algorithm is proposed based on the SVM feature matching algorithm, firstly on the basis of the traditional feature selection, the paper put forward 3 d feature selection method, so as to improve the precision of detection, secondly uses RBF kernel as the kernel function of SVM feature matching algorithm, and finally divides the test process into iterative detection and smooth detection. Simulation experiments show that characteristic matching based on mobile P2P network data flow control algorithm has a higher recognition rate and better scalability

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Section: Introductionmentioning

confidence: 99%

Data Flow Control Algorithm based on Feature Matching in Mobile P2P Network

Zhang¹,

Shen²

2013

JNW

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“…Reactive P2P worms infect only peers which are requesting files at that time [7]. Active P2P worm has a non-scanning feature and can make use of neighbor routing table of P2P network as attacking list to launch an attack [8]. Although there are currently only passive P2P worms in the wild such as Igloo and MyDoom, active P2P worms will prevail in the future.…”

Section: Introductionmentioning

confidence: 99%

Stability Analysis of P2P Worm Propagation Model with Dynamic Quarantine Defense

Yang

Chang²,

Yao³

et al. 2011

JNW

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The propagation of P2P worm covers large area and causes great damage. A dynamic quarantine protocol is designed to quarantine the suspicious host in the P2P system. Then a mathematical model of PWPQ is proposed which considering the dynamic process of peer joining and leaving. The effect of dynamic quarantine on active P2P worm is analyzed. Through stability analysis for PWPQ model, a key argument of infection-free stable point which affect the P2P worm propagation, the basic reproduction number, is deduced. Simulation results show that the propagation model of P2P worms can reflect the P2P worm behaviors and the performance of our model is significantly better than other models, in terms of decreasing the number of infected hosts and reducing the worm propagation speed. When the basic reproduction number is less than 1, infection-free stable point is global stability and the P2P worm are eliminated. The PWPQ model gives some way to cont...

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