Robust rs research a The goal of robust recommendation is to prevent attackers from manipulating an rs through large-scale insertion of false user profiles: a profile injection attack An attack is a concerted effort to bias the results of a recommender system by the insertion of a large number of profiles using false identities or sybils a Each identity is referred to as an attack profile a Research has concentrated on attacks designed to achieve a particular recommendation outcome
Tutorial on Robustness of Recommender Systems What is Robustness? Profile Injection Attacks Robust RS Research The goal of robust recommendation is to prevent attackers from manipulating an RS through large-scale insertion of false user profiles: a profile injection attack An attack is a concerted effort to bias the results of a recommender system by the insertion of a large number of profiles using false identities or sybils. Each identity is referred to as an attack profile. Research has concentrated on attacks designed to achieve a particular recommendation outcome A Product Push attack: attempt to secure positive recommendations for an item or items; A Product Nuke attack: attempt to secure negative recommendations for an item or items. We can also think of attacks that aim to simply destroy the accuracy of the system. RecSys 2011: Tutorial on Recommender Robustness
Robust rs research a The goal of robust recommendation is to prevent attackers from manipulating an rs through large-scale insertion of false user profiles: a profile injection attack An attack is a concerted effort to bias the results of a recommender system by the insertion of a large number of profiles using false identities or sybils a Each identity is referred to as an attack profile Research has concentrated on attacks designed to achieve particular recommendation outcome a A Product Push attack: attempt to secure positive recommendations for an item or items
Tutorial on Robustness of Recommender Systems What is Robustness? Profile Injection Attacks Robust RS Research The goal of robust recommendation is to prevent attackers from manipulating an RS through large-scale insertion of false user profiles: a profile injection attack An attack is a concerted effort to bias the results of a recommender system by the insertion of a large number of profiles using false identities or sybils. Each identity is referred to as an attack profile. Research has concentrated on attacks designed to achieve a particular recommendation outcome A Product Push attack: attempt to secure positive recommendations for an item or items; A Product Nuke attack: attempt to secure negative recommendations for an item or items. We can also think of attacks that aim to simply destroy the accuracy of the system. RecSys 2011: Tutorial on Recommender Robustness
Robust rs research a The goal of robust recommendation is to prevent attackers from manipulating an rs through large-scale insertion of false user profiles: a profile injection attack An attack is a concerted effort to bias the results of a recommender system by the insertion of a large number of profiles using false identities or sybils a Each identity is referred to as an attack profile Research has concentrated on attacks designed to achieve particular recommendation outcome a A Product Push attack: attempt to secure positive recommendations for an item or items, a A Product Nuke attack: attempt to secure negative recommendations for an item or items
Tutorial on Robustness of Recommender Systems What is Robustness? Profile Injection Attacks Robust RS Research The goal of robust recommendation is to prevent attackers from manipulating an RS through large-scale insertion of false user profiles: a profile injection attack An attack is a concerted effort to bias the results of a recommender system by the insertion of a large number of profiles using false identities or sybils. Each identity is referred to as an attack profile. Research has concentrated on attacks designed to achieve a particular recommendation outcome A Product Push attack: attempt to secure positive recommendations for an item or items; A Product Nuke attack: attempt to secure negative recommendations for an item or items. We can also think of attacks that aim to simply destroy the accuracy of the system. RecSys 2011: Tutorial on Recommender Robustness
Robust rs research a The goal of robust recommendation is to prevent attackers from manipulating an rs through large-scale insertion of false user profiles: a profile injection attack An attack is a concerted effort to bias the results of a recommender system by the insertion of a large number of profiles using false identities or sybils a Each identity is referred to as an attack profile Research has concentrated on attacks designed to achieve particular recommendation outcome a A Product Push attack: attempt to secure positive recommendations for an item or items, a A Product Nuke attack: attempt to secure negative recommendations for an item or items a We can also think of attacks that aim to simply destroy the accuracy of the syste
Tutorial on Robustness of Recommender Systems What is Robustness? Profile Injection Attacks Robust RS Research The goal of robust recommendation is to prevent attackers from manipulating an RS through large-scale insertion of false user profiles: a profile injection attack An attack is a concerted effort to bias the results of a recommender system by the insertion of a large number of profiles using false identities or sybils. Each identity is referred to as an attack profile. Research has concentrated on attacks designed to achieve a particular recommendation outcome A Product Push attack: attempt to secure positive recommendations for an item or items; A Product Nuke attack: attempt to secure negative recommendations for an item or items. We can also think of attacks that aim to simply destroy the accuracy of the system. RecSys 2011: Tutorial on Recommender Robustness
Robust rs research We assume that the attacker has no direct access to the ratings database manipulation achieved via the creation of false profiles only
Tutorial on Robustness of Recommender Systems What is Robustness? Profile Injection Attacks Robust RS Research We assume that the attacker has no direct access to the ratings database – manipulation achieved via the creation of false profiles only. We ignore system-level methods (e.g. Captchas) for preventing the generation of false identities or ratings Focus is on the recommendation algorithm’s ability to resist manipulation either by Identifying false profiles from their statistical properties and ignoring or lessening their impact on the generation of recommendations; or Generating recommendations in a manner that is inherently insensitive to manipulation. RecSys 2011: Tutorial on Recommender Robustness