發(fā)布時(shí)間：2018-04-03 19:48

  本文選題：Web服務(wù)　切入點(diǎn)：服務(wù)選擇　出處：《海軍工程大學(xué)學(xué)報(bào)》2017年02期

【摘要】：針對(duì)由于Web服務(wù)推薦用戶提交虛假Q(mào)oS反饋而導(dǎo)致的QoS預(yù)測(cè)準(zhǔn)確度下降問(wèn)題,提出了一種基于Beta信譽(yù)模型的虛假Q(mào)oS反饋濾除算法。該算法首先將若干個(gè)經(jīng)過(guò)認(rèn)證的中心用戶作為初始可信用戶集;然后,評(píng)估用戶反饋數(shù)據(jù)與可信用戶集反饋數(shù)據(jù)的偏離程度;最后,根據(jù)用戶提交的偏離反饋次數(shù)對(duì)其信譽(yù)度進(jìn)行評(píng)估,并將信譽(yù)度高于可信閾值的用戶判定為可信用戶,使可信用戶集得到更新。通過(guò)循環(huán)執(zhí)行以上過(guò)程,大部分虛假用戶將被分離出系統(tǒng)。實(shí)驗(yàn)結(jié)果表明:該算法具有較強(qiáng)的虛假用戶篩查能力,可有效提升QoS預(yù)測(cè)算法的抗攻擊能力。
[Abstract]:Because the QoS prediction of Web service recommendation user submitted false feedback QoS caused a decline in the problem accurately, a false QoS Beta reputation model based on the feedback filtering algorithm. Firstly, a plurality of user authentication through the centre as the initial set of trusted users; then, user feedback and evaluation data set of trusted user feedback the degree of deviation from the data; finally, according to the user submitted from feedback times on the credibility evaluation, and the credibility is higher than the threshold for the user to determine the trusted trusted users to trusted users set updated. Through the cycle of the implementation of the above process, most of the false users will be isolated from the system. The experimental results show that the algorithm has false screening ability of the user, can effectively improve the QoS prediction algorithm anti attack capability.

【作者單位】： 海軍工程大學(xué)裝備經(jīng)濟(jì)管理系;
【基金】：國(guó)家部委基金資助項(xiàng)目(9140A04020215JB11050)
【分類號(hào)】：TP393.09
，

本文編號(hào)：1706653