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

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

doi:10.1016/j.asoc.2015.04.053

Cited by 37 publications

(23 citation statements)

References 51 publications

(74 reference statements)

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“…Generation by generation, successful populations are evolved in new generations to create improved possible solutions. The quality of solutions is expressed by applying a fitness function [20,21].…”

Section: Methodsmentioning

confidence: 99%

International carbon market price forecasting using an integration model based on SVR

Jiang¹,

Wu²

2015

Proceedings of the 2015 International Conference on Engineering Management, Engineering Education and Information Technology

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Abstract. Better forecast of carbon emission prices may increase risk control capabilities of emission market stakeholders, and provide decision support for policy makers, financial institutions and enterprises. However, the issue of carbon price forecasting is complicated and several existing prediction models are difficult to achieve satisfactory results. This paper proposes an integration model based on SVR to predict international carbon market price. The model we suggest includes two steps: we respectively establish ARIMA, BP neural network, grey model GM(1,1) and genetic programming to fit the original sequence of the carbon price at the first phase, and get four prediction results. Additionally, SVR is used to integrate these four results and eventually obtain prediction result. For verification and testing, EUA (DEC15) carbon price from December 3, 2012 to April 10, 2015 under the EU ETS was used to examine the forecasting ability of the proposed integration model. The result demonstrates the accuracy of integration model proposed in this paper is superior to the other three basic models.

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Section: Methodsmentioning

confidence: 99%

International carbon market price forecasting using an integration model based on SVR

Jiang¹,

Wu²

2015

Proceedings of the 2015 International Conference on Engineering Management, Engineering Education and Information Technology

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“…Trust mechanism is essential for the mobile nodes to evaluate the trustworthiness among the mobile nodes and interact selectively with more reputable ones [12], to encourage interacting among the mobile nodes and combat malicious behaviors. In the papers of [13,14], the authors propose some trust evaluating and reasoning methods using probability models.…”

Section: Related Workmentioning

confidence: 99%

“…where a down is the sub-level's downside of the service requirement satisfaction degree, n sub is the interaction number of the sub-level, n total is the total interaction number, s level is the service level, and τ is the width of the sub-level. Then, we use (11), (12), and (21) to generate the trust relationship of cloud numeral characteristics (E(x), Δ S(x), ΔHS(x)), which is shown in Table III.…”

Section: The Case Initializationmentioning

confidence: 99%

A novel membership cloud model‐based trust evaluation model for vehicular ad hoc network of T‐CPS

Sun

Zhao

Cheng

2016

Security Comm Networks

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It is generally known that the trust relationships among mobile nodes of vehicular ad hoc network (VANET) are uncertain in transportation cyber-physical system (T-CPS). However, the existing researches could not accurately describe the uncertainty in their trust evaluation models. To solve this problem, we propose a novel membership cloud-based trust evaluation model for VANET of T-CPS. The proposed model considers the trust uncertainty of fuzziness and randomness in the interactions among vehicles and uses membership cloud to describe the uncertainty in unified formats. Besides, we give the detail description of trustworthiness as well as algorithm to calculate the cloud droplets and the aggregated trust evaluation values. An experiment of study case demonstrates that our trust model can perfectly describe trust relationship among vehicles from the quantitative data to the qualitative information, and also vice versa. Thus, our trust model can accurately describe the uncertainty of fuzziness and randomness of the trust relationships. Meanwhile, two typical scenarios simulation and comparison with other up to date models demonstrate the validity and practicality of our trust model among vehicles for VANET of T-CPS.

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“…Guo et al [16] classified fuzzy data over the maximum tree with fuzzy clustering for large-scale P2P networks to improve performance. GenTrust [17] evaluates service and reputation contexts separately and uses peer and interaction features as input for genetic programming computation to detect malicious peers. Liu et al [18] proposed a trust model based on machine learning and used real datasets from eBay and Allegro.…”

Section: Related Workmentioning

confidence: 99%

Consistency-based trust management in P2P networks

Şahin¹,

Can²

2018

Turk J Elec Eng & Comp Sci

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Abstract:Detecting malicious peers is a challenging task in peer-to-peer networks due to their decentralized structure and lack of central authority. Trust models can help identify malicious peers by maintaining information about peer relations and interactions. Keeping information about trust relations helps to reduce risks when providing or using services. This paper introduces two consistency concepts in trust management. Feedback consistency is used to evaluate how consistent feedback is with respect to past feedbacks. On the other side, peer consistency measures consistency of a peer's past feedbacks. These metrics help to reduce malicious interactions and increase successful downloads. Furthermore, the model offers better service quality for good peers by using consistency metrics. A file-sharing application is implemented on a simulation environment. The proposed model can effectively reduce the malicious download rate, even in 50% malicious environments, and increases successful download rates.

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

Cited by 37 publications

References 51 publications

International carbon market price forecasting using an integration model based on SVR

International carbon market price forecasting using an integration model based on SVR

A novel membership cloud model‐based trust evaluation model for vehicular ad hoc network of T‐CPS

Consistency-based trust management in P2P networks

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