A pre-evolutionary advisor list generation strategy for robust defensing reputation attacks

作者：

Highlights：

• Our approach better estimate trustworthiness of sellers and reducing risk.

• Pre-evolution algorithm searching for optimal customized advisor lists.

• Evaluating by buyer's own experience and seller's recent reviewers.

• Superior in robustness, accuracy and stability under multifarious attacks.

摘要

•Our approach better estimate trustworthiness of sellers and reducing risk.•Pre-evolution algorithm searching for optimal customized advisor lists.•Evaluating by buyer's own experience and seller's recent reviewers.•Superior in robustness, accuracy and stability under multifarious attacks.

论文关键词：Trust and reputation systems,Unfair rating attacks,Robust trust network,Evolutionary algorithm

论文评审过程：Received 3 November 2015, Revised 17 February 2016, Accepted 19 March 2016, Available online 9 April 2016, Version of Record 5 May 2016.

论文官网地址：https://doi.org/10.1016/j.knosys.2016.03.015