Specifically, SybilSCAR is Scalable, Convergent, Accurate, and Robust to label noise. framework, each structure-based method can be viewed as iteratively applying a local rule to every node, which propagates label information from the training dataset to other nodes in the social network.
Under our framework, these methods can be viewed as iteratively applying a (different) local rule to every user, which propagates label information among a ...
Under our framework, these methods can be viewed as iteratively applying a (different) local rule to every user, which propagates label information among a ...
Abstract—Detecting Sybils in online social networks (OSNs) is a fundamental security research problem as adversaries can leverage Sybils to perform various ...
SybilSCAR, a novel structure-based method to detect Sybils in social networks, is proposed and shown to be substantially more accurate and more robust to ...
Mar 12, 2018 · Under our framework, these methods can be viewed as iteratively applying a (different) local rule to every user, which propagates label ...
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Structure-based Sybil/fake account detection in online social networks. The codes implement the SybilBelief, SybilRank, SybilSCAR, and GANG algorithms.
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Mar 13, 2018 · In this work, we propose SybilSCAR, a novel structure-based method to detect Sybils in social networks. SybilSCAR is Scalable, Convergent ...
Binghui Wang, Le Zhang, and Neil Zhenqiang Gong. "SybilSCAR: Sybil Detection in Online Social Networks via Local Rule based Propagation", in INFOCOM, 2017.
This paper focuses on graph-based detection methods. Theoretically, an underlying assumption for graph-based Sybil-detection methods is that the benign ...