Big Enough to Care Not Enough to Scare! Crawling to Attack Recommender Systems
2020
Online recommendation services, such as e-commerce sites, rely on a vast amount of knowledge about users/items that represent an invaluable resource. Part of this acquired knowledge is public and can be accessed by anyone through the Internet. Unfortunately, that same knowledge can be used by competitors or malicious users. A large body of research proposes methods to attack recommender systems, but most of these works assume that the attacker knows or can easily access the rating matrix. In practice, this information is not directly accessible, but can only be gathered via crawling.
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