Attacks and Remedies in Collaborative Recommendation

Collaborative-filtering recommender systems are an electronic extension of everyday social recommendation behavior: people share opinions and decide whether or not to act on the basis of what they hear. Collaborative filtering lets you scale such interactions to groups of thousands or even millions. Publicly accessible user-adaptive systems such as collaborative recommender systems introduce security issues that must be solved if users are to perceive these systems as objective, unbiased, and accurate.