Location : AttResRec: Learning User Credibility for ...
题目：AttResRec: Learning User Credibility for Attack Resistant Matrix Factorization Recommendation
时间：2025年6月11日（周三）9:00-9:40
地点：中科院数学院南楼N212
报告人：张文（北京工业大学）
报告摘要：
The pervasive threat of shilling attacks, where malicious users inject fraudulent ratings to manipulate recommendations, critically undermines the reliability of Matrix Factorization (MF)-based recommender systems. This paper proposes AttResRec, a novel MF-based approach designed to improve system integrity by learning and integrating user credibility directly into the recommendation pipeline. AttResRec's defense is built upon three synergistic innovations. First, it employs a user credibility estimation mechanism that quantifies user credibility by assessing the consistency between an individual's interaction history and prevalent item co-occurrence patterns identified from collective user behavior. This directly enables differentiation between genuine and potentially malicious users. Second, the learned credibility dynamically informs a Credibility-Aware Huber Loss (CHL) function. The CHL adaptively modifies its error sensitivity, rigorously penalizing deviations for high-credibility users while robustly limiting the influence of large errors associate with low-credibility users. Third, the model optimization is performed via Credibility-Weighted Stochastic Gradient Descent (CW-SGD), ensuring that users with lower credibility scores exert a diminished influence on the learned model parameters. Extensive experiments on the MovieLens-25M and Amazon Music Instrument datasets, under diverse shilling attack scenarios, demonstrate AttResRec's benefits. That is, it not only achieves superior recommendation accuracy but also exhibits enhanced attack resistance, evidenced by lower prediction shift and hit ratios for poisoned items in poisoned environments, compared to state-of-the-art robust baselines.
报告人简介：
张文, 北京工业大学经济管理学院管理学科学与工程系教授，博士生导师。2009 年4月毕业于日本北陆先端科学技术大学院大学知识科学研究科并获得知识科学博士学位。主要研究领域为决策支持系统、人工智能和机器学习。曾先后主持国家自然科学基金面上项目（2项）、国家自然科学基金青年项目（1项）、北京市自然科学基金面上项目（2项）和北京市哲学社会科学基金一般项目（1项）。目前兼任亚太人工智能 PRICAI 和 IEEE SMC 国际会议的程序委员，国际先进人工智能会议（AAAI）程序委员、中国系统工程学会（SESC）数据科学与知识系统工程专委、中国计算学会（CCF）服务计算专委、中国人工智能学会（CAAI）社会计算专委，中国决策科学学会理事。近年来已经在相关领域国际国内重要期刊上发表相关 SCI/SSCI/CSSCI 文章90余篇，如IEEE Transactions on Neural Networks and Learning Systems, IEEE Journal on Internet of Things, IEEE Transactions on Reliability, IEEE Transactions on Social Computational Systems, Decision Support Systems, Journal of Business Research, 系统工程理论与实践等。
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