计算机工程与科学2013，Vol.35Issue(8)：174-179,6.DOI:10.3969/j.issn.1007-130X.2013.08.028
一种基于混合策略的推荐系统托攻击检测方法
A shilling attacks detection method of recommender systems based on hybrid strategies
摘要
Abstract
Detecting shilling attacks for recommender systems is necessary to solve problems such as imbalanced dataset and cost sensitive,but existing methods are lack of relative studies.This paper propose a new attack detection method,which combines the methods of under-sampling and cost-sensitive support vector machine together.Firstly,according to the different importance for classification to process,the training dataset is balanced by sample importance based under-sampling technique,for the sake of eliminating a lot of noise samples while retaining the most of useful samples.Secondly,cost-sensitive support vector machine is conducted to train the reconstructed dataset.Finally,the detection decision function is obtained.Experimental results show that the proposed method can improve the accuracy of detecting shilling attacks and has a strong generality.关键词
推荐系统/托攻击/不均衡数据集/代价敏感学习/欠采样/支持向量机Key words
recommender system/ shilling attack/ unbalanced data/ cost-sensitive learning/ under-sampling/ support vector machine分类
信息技术与安全科学引用本文复制引用
吕成戍,王维国..一种基于混合策略的推荐系统托攻击检测方法[J].计算机工程与科学,2013,35(8):174-179,6.基金项目
国家社会科学基金青年项目(11CJY008) （11CJY008）
辽宁省社会科学规划基金项目(L10BJL026) （L10BJL026）
中央高校专项科研基金(DUT10RW302) （DUT10RW302）
