TrustDavis: A Non-Exploitable Online Reputation System
CEC '05 Proceedings of the Seventh IEEE International Conference on E-Commerce Technology
Proceedings of the 4th Workshop on Social Network Systems
Canal: scaling social network-based Sybil tolerance schemes
Proceedings of the 7th ACM european conference on Computer Systems
Aiding the detection of fake accounts in large scale social online services
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Key challenges in defending against malicious socialbots
LEET'12 Proceedings of the 5th USENIX conference on Large-Scale Exploits and Emergent Threats
Design and analysis of a social botnet
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Online social networking sites (OSNs) like Facebook and Orkut contain personal data of millions of users. Many OSNs view this data as a valuable asset that is at the core of their business model. Both OSN users and OSNs have strong incentives to restrict large scale crawls of this data. OSN users want to protect their privacy and OSNs their business interest. Traditional defenses against crawlers involve rate- limiting browsing activity per user account. These defense schemes, however, are vulnerable to Sybil attacks, where a crawler creates a large number of fake user accounts. In this paper, we propose Genie, a system that can be deployed by OSN operators to defend against Sybil crawlers. Genie is based on a simple yet powerful insight: the social network itself can be leveraged to defend against Sybil crawlers. We first present Genie's design and then discuss how Genie can limit crawlers while allowing browsing of user profiles by normal users.