一種集成直覺模糊信息的激勵自適應信任模型
doi: 10.11999/JEIT150750 cstr: 32379.14.JEIT150750
基金項目:
國家自然科學基金(71361012, 61263018)，江西省教育廳科學技術研究項目(GJJ15267)，江西省高校人文社會科學研究項目(JC1338)，江西財經(jīng)大學青年基金
Incentive Adaptive Trust Model Based on Integrated Intuitionistic Fuzzy Information
Funds:
The National Natural Science Foundation of China (71361012, 61263018), The Science and Technology Project of Jiangxi province educational department of China (GJJ151601), The Colleges Humanities Social Science Research Project of Jiangxi Province (JC1338), The Young Foundation of Jiangxi University of Finance and Economics
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摘要: 針對現(xiàn)有信任機制不能很好表達信任的不確定性，且缺乏有效處理分布式網(wǎng)絡中存在的不誠實推薦和策略性欺騙等問題，該文提出一種集成直覺模糊信息的自適應信任評估模型。為了激勵提供可信服務的實體，懲罰不良行為實體，該模型結合服務持續(xù)性強度和時間衰減因子，計算實體直接信任直覺模糊數(shù)。同時利用實體的推薦可信度和行為一致性過濾不誠實推薦行為。除此之外，為了克服綜合信任聚合計算中權重確定較主觀的問題，給出了一種新的自適應權重分配方法。仿真實驗表明，該模型在提高實體服務積極性和抑制惡意欺詐行為中，都有較好的適應性和有效性。
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關鍵詞:
- 直覺模糊信息 /
- 信任模型 /
- 分布式網(wǎng)絡 /
- 推薦可信度
Abstract: Existing trust models can not effectively express the uncertainty of trust relationship and deal with such issues as dishonest feedbacks and strategic frauds from malicious entities in the distributed network, an adaptive trust model based on aggregating Intuitionistic Fuzzy Information (IFI) is proposed. Firstly, in order to incentivize entities providing trustworthy service and punish entities taking along malicious behavior, an approach on aggregating IFI is constructed to compute the direct trust intuitionistic fuzzy numbers which contain the latest permanence factor and the time decay factor. Then, the recommendation credibility and uniformity are defined to detect dishonest recommendation. Subsequent, an adaptive weighted approach is developed to avoid distributing the weights of direct and indirect trust subjectively. The simulation experiments demonstrate that the proposed model not only is robust on malicious attacks, but also has better adaptability and effectiveness. -
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