SybilRank

We introduce a new tool in the hands of OSN operators, which we call SybilRank . It relies on social graph properties to rank users according to their perceived likelihood of being fake (Sybils). SybilRank is computationally efficient and can scale to graphs with hundreds of millions of nodes, as demonstrated by our Hadoop prototype. We deployed SybilRank in Tuenti’s operation center. We found that ∼90% of the 200K accounts that SybilRank designated as most likely to be fake, actually warranted suspension. On the other hand, with Tuenti’s current user-report-based approach only ∼5% of the inspected accounts are indeed fake.

https://gyazo.com/cdc9b35a99ccc5919bdb81c4ffd7dd33

(DeepL) We present a new tool, which we call SybilRank, in the hands of OSN operators. This tool uses properties of the social graph to rank users according to their likelihood of being imposters (Sybils).SybilRank is computationally efficient and scalable to graphs with hundreds of millions of nodes, as demonstrated in our Hadoop prototype. We deployed SybilRank in our Tuenti operations center. We found that of the 200,000 accounts that SybilRank identified as likely fakes, about 90% actually had to be suspended. In contrast, Tuenti's current user-report-based approach found that only about 5% of the accounts inspected were truly fake.

SybilRank is computationally efficient... Scalable to graphs with hundreds of millions of nodes

https://gyazo.com/cdc9b35a99ccc5919bdb81c4ffd7dd33

How can "accounts that correspond to retinal scans" be "Trust Seeds" with a high degree of trust?

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