Crawling Attacks Against Web-based Recommender Systems

13 years 6 months ago

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—User proﬁles derived from Web navigation data are used in important e-commerce applications such as Web personalization, recommender systems, and Web analytics. In the open environment of the Internet, malicious third parties may seek to manipulate the output of such applications (such as the suggestions produced by a recommender system) by manipulating the input, through the generation of false user navigation proﬁles. Recent research has shown that systems using explicit ratings input by users are highly vulnerable to such “proﬁle injection” attacks. Malicious users can cause certain products to be recommended more frequently and others less frequently. We show that Web recommenders that use implicit Web navigation proﬁles to learn user preference models, despite using different algorithms than traditional recommenders based on explicit ratings, are nevertheless subject to similar manipulation. We examine the impact of “crawling attacks” against navigation-based We...

Runa Bhaumik, Robin D. Burke, Bamshad Mobasher

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