SybilWalk：Random Walk based Fake Account Detection in Online Social Networks论文笔记

时间 2021-01-02

标签异常检测繁體版

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1. Random Walk based Methods 基于随机游走的方法旨在利用Online Social Networks 的Social Structure，因为我们通常认为，尽管攻击者可以任意控制Sybils之间的连接，但是攻击者很难操作benign node和Sybils之间的连接，因为这种需要benign node的操作。因此，benign node与Sybils之间存在struct

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1. SynchroTrap：Uncovering Large Groups of Active Malicious Accounts in Online Social Networks（论文笔记）
2. 论文笔记：Friend Recommendation Considering Preference Coverage in Location-Based Social Networks
3. 论文笔记：DeepWalk: Online Learning of Social Representations
4. Deep learning-based personality recognition from text posts of online social networks 阅读笔记
5. (2015)Anomaly detection in dynamic networks : a survey 论文笔记
6. 论文笔记----DeepWalk: Online Learning of Social Representations
7. Anomaly Detection in Online Social Network: A Survey
8. 论文阅读：Fake News Detection on Social Media:A Data Mining Perspective
9. 【论文笔记 Detection】OHEM: Training Region-based Object Detectors with Online Hard Example Mining
10. 论文笔记01 Sign prediction by motif naive bayes model in social networks

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