{"paper":{"title":"SybilFuse: Combining Local Attributes with Global Structure to Perform Robust Sybil Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"cs.CR","authors_text":"Binghui Wang, Kurt Thomas, Neil Zhenqiang Gong, Peng Gao, Prateek Mittal, Sanjeev R. Kulkarni","submitted_at":"2018-03-19T01:14:06Z","abstract_excerpt":"Sybil attacks are becoming increasingly widespread and pose a significant threat to online social systems; a single adversary can inject multiple colluding identities in the system to compromise security and privacy. Recent works have leveraged social network-based trust relationships to defend against Sybil attacks. However, existing defenses are based on oversimplified assumptions about network structure, which do not necessarily hold in real-world social networks. Recognizing these limitations, we propose SybilFuse, a defense-in-depth framework for Sybil detection when the oversimplified as"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.06772","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}