Evolving a Trust Model for Peer-to-Peer Networks Using Genetic Programming

Tahta, Ugur Eray; Can, Ahmet Burak; Şen, Sevil

doi:10.1007/978-3-662-45523-4_1

Cited by 5 publications

(3 citation statements)

References 17 publications

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“…The amount of free‐rider was reduced, and the peers were enabled to share their own resource. Tahta et al investigated the usage of genetic programming approach and evaluated the trustworthiness of the peers without requiring a central authority. A trust management model was proposed based on the previous interactions and recommendations.…”

Section: Related Workmentioning

confidence: 99%

PSO‐based optimal peer selection approach for highly secure and trusted P2P system

Nallakannu¹,

Thiagarajan²

2016

Security Comm Networks

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There is a significant growth of the peer-to-peer (P2P) systems over the last few years because of their high potential for sharing file among the peers. Selection of the optimal peer ensures high data transmission rate and reduced network cost. However, it is highly difficult to select the optimal peer because of the variation in the heterogeneous capacity and dynamic capacity of the peers. Efficient peer selection approach is highly required to overcome this difficulty. This paper proposes a particle swarm optimization (PSO)-based optimal peer selection approach for a highly secure and trusted P2P system, based on the bandwidth and trust level of the peers. File replication is performed to effectively tackle the overloading of the hot files. Replacement of the replicated file is performed, based on their demand rates. The success rate and bandwidth rate of the peer are computed. Bandwidth and trust-based PSO is applied to select the optimal peer. This improves the success rate for the peer transmission. After selecting the optimal peer, the replicated file is encrypted and transmitted to the selected peer. Finally, the replicated file is decrypted. Our proposed approach achieves minimum average query delay and ensures a highly secure and trusted environment for the P2P systems. The performance of the proposed approach is evaluated by comparing the proposed approach with the existing techniques. From the comparison results, it is clearly evident that the proposed approach achieves higher success rate and lower link stress, delay, communication overhead, finished time and network cost.

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Section: Related Workmentioning

confidence: 99%

PSO‐based optimal peer selection approach for highly secure and trusted P2P system

Nallakannu¹,

Thiagarajan²

2016

Security Comm Networks

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“…This paper proposes a genetic programming (GP) based trust management model (GenTrust), extending our previous work [4] with greater experimental verification and analysis on features. The proposed model helps to identify malicious peers and find trustworthy peers using the features derived from peer interactions and recommendations.…”

Section: Q3mentioning

confidence: 99%

GenTrust: A genetic trust management model for peer-to-peer systems

Tahta

Şen

Can

2015

Applied Soft Computing

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“…While MEP (a technique that allows us to encode multiple expressions) is more successful in the identification of some attack types, LGP is better in the detection of other types. Tahta et al (2014) employ GP in order to differentiate malicious peers from benign ones in peer-to-peer (P2P) networks. They run P2P simulation for each individual to see how derived solutions are effective in preventing malicious peers from participating in the network.…”

Section: Intrusion Detection On Conventional Networkmentioning

confidence: 99%