A pre-evolutionary advisor list generation strategy for robust defensing reputation attacks
详细信息 查看全文
- 作者：Shu-juan Jia ; jane_ji2003@aliyun.com" class="auth_mail" title="E-mail the corresponding author ; Hai-yan Maa ; 295340370@qq.com" class="auth_mail" title="E-mail the corresponding author ; Shu-lian Zhangb ; 958007736@qq.com" class="auth_mail" title="E-mail the corresponding author ; Ho-fung Leungc ; lhf@cuhk.edu.hk" class="auth_mail" title="E-mail the corresponding author ; Dickson Chiud ; dicksonchiu@ieee.org" class="auth_mail" title="E-mail the corresponding author ; Chun-jin Zhange ; zhangchjin@163.com" class="auth_mail" title="E-mail the corresponding author ; Xian-wen Fangf ; fangxianwen@hotmail.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Trust and reputation systems ; Unfair rating attacks ; Robust trust network ; Evolutionary algorithm
- 刊名：Knowledge-Based Systems
- 出版年：2016
- 出版时间：1 July 2016
- 年：2016
- 卷：103
- 期：Complete
- 页码：1-18
- 全文大小：4039 K
文摘
- class="listitem" id="list_celist0001">
- class="label">•
Our approach better estimate trustworthiness of sellers and reducing risk.
- class="label">•
Pre-evolution algorithm searching for optimal customized advisor lists.
- class="label">•
Evaluating by buyer's own experience and seller's recent reviewers.
- class="label">•
Superior in robustness, accuracy and stability under multifarious attacks.