2020/08/19 by Amir Jalaly Bidgolya, Bidgolya, Amir Jalaly, Zoleikha Rahmaniana +1
Computer Science · #Advanced Malware Detection Techniques #Computers and Society (cs.CY) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Network Security and Intrusion Detection #Social and Information Networks (cs.SI) #Spam and Phishing Detection
paper · pdf · doi:10.48550/arxiv.2008.08650
openalex publication_date 2020/08/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Online reviews are potent sources for industry owners and buyers, however opportunistic people may try to destruct or promote their desired product by publishing fake comments named spam opinion. So far, many models have been developed to detect spam opinions, but none have addressed the issue of spam attack. It is a way a smart spammer can deceive the system in a manner in which he can continue generating spams without the fear of being detected and blocked by the system. In this paper, the spam attacks are discussed. Moreover, a robust graph-based spam detection method is proposed. The method respectively estimates honesty, trust and reliability values of reviews, reviewers, and products considering possible deception scenarios. The paper also presents the efficiency of the proposed method as compared to other graph-based methods through some case studies.