Email this article 
Network Trustworthy Assessment Based on Advanced DyTrust Model
(*) Corresponding author
DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)
Abstract
According to the algorithm of direct trust value in DyTrust Model, a time attenuation factor was presented, and the influence of time factor was considered. At the same time, a risk function was put forward, and a new model named A-DyTrust was proposed. Based on the proportional relationship to the quality and risk of request services by node, a formula of the risk function was raised to improve the DyTrust Model. The simulation results show that A-DyTrust Model is more effective than DyTrust Model, which has better dynamic adaptive capacity, higher ability to detect malicious nodes and more effectively aggregate capacity of the information than DyTrust Model. Aim at the question of network trust rating, a method of assessment for network trustworthy based on the associative memory capability of the Hopfield Neural Network was given. The simulation results show that this method can determine the level of trust of current network accurately, then achieve the quantification of network trust.
Copyright © 2013 Praise Worthy Prize - All rights reserved.
Keywords
References
T.Beth，M.Borcherding B.Klein. Valuation of trust in open networks.In Proceedings of the European Symposium on Research in Computer Security. Springer-Verlag Brighton UK.1994:3-18.
Josang,Audun,Ismail,Roslan,Boyd,Colin A.A survey of trust and reputation systems for online service provision. Decision Support Systems,2007.43 (2):618-644.
L.Xiong, L.Liu. PeerTrust:Supporting reputation-based trust in peer-to-peer communities, IEEE Transactions on Data and Kownledge Engineering,Special Issue on peer-topeer Based data Management,July 2004,16(7):843-857.
S.Stefan, S.Robert. Fuzzy trust evaluation and credibility development in multi2agent systems. Applied Soft Computing, 2007,7(2):4922505.
Theodorakopoulos G,Baras J s. On trust models and trust evaluation metrics for ad-hoc networks. IEEE Journal on Selected Areas in Communications.2006.24(2):318-328.
Xiaoyong Li, Xiaoli Gui. Trust quantitative model of trust network with multiple decision. Journal of computers, 2009, 32(3):405-416
Xiaoyong Li, Xiaoli Gui, Qian Mao, Dongqi Leng. Trust quantitative model of trust network with multiple decision. Journal of computers, 2009, 32(3):664-674.
Zhiguo Shi, Yiwei Liu, Zhiliang Wang. Dynamic P2P trust model based on feedback mechanism of the time window. Journal of communications, 2010, 31(2):120-129.
Zhengqiang Liang, Weisong Shi. Enforcing cooperative resource sharing in unt rusted Peer-to-Peer environments. Journal of Mobile Networksand Applications-Springer, 2005,10(6):771-783.
Leitao Guo, Shoubao Yang, Jing Wang. Distributed trust model of P2P networks based on vector space. Computer research and development, 2006, 43(9):1564-1570.
Wen Tang. Trust management based on fuzzy set theory. Beijing University, 2003.
Xiaolin Gui, Bing Xie Yinan ,Li,et al. Study on the behavior-based trust model in grid security systems.The 2004 IEEE Int'l Conf on Services Computing, Washington, DC,200
D.Cvrcek. Dynamics of reputation. In: Proceedings of the 9th Nordic Workshop on Secure IT-systems(Nordsec’04), Helsin-ki, FI, 2004, 1~14.
M.K.Darwish, D.Daniolos, A.Janbey, A Fully Digital Neural Network Based Optimised Pulse Width Modulator. ICMTMA, 2008.8,49~53.
M.A.Azgomi, A.Mov, An Introduction to High-Level Stochastic Activity Networks.ICMTMA, 2006.6, 20~30.
Sabir Messalti, Shahrokh Saadate, Ahmed Gherbi, Damien Flieller. Neural Networks for Assessment Power System Transient Stability,.ICMTMA,2010.6,381-387.
Refbacks
- There are currently no refbacks.
Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize
