SybilWalk：Random Walk based Fake Account Detection in Online Social Networks論文筆記
1. Random Walk based Methods 基於隨機遊走的方法旨在利用Online Social Networks 的Social Structure，因爲我們通常認爲，儘管攻擊者可以任意控制Sybils之間的連接，但是攻擊者很難操作benign node和Sybils之間的連接，因爲這種需要benign node的操作。因此，benign node與Sybils之間存在struct
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相關文章
- 1. SynchroTrap：Uncovering Large Groups of Active Malicious Accounts in Online Social Networks（論文筆記）
- 2. 論文筆記：Friend Recommendation Considering Preference Coverage in Location-Based Social Networks
- 3. 論文筆記：DeepWalk: Online Learning of Social Representations
- 4. Deep learning-based personality recognition from text posts of online social networks 閱讀筆記
- 5. (2015)Anomaly detection in dynamic networks : a survey 論文筆記
- 6. 論文筆記----DeepWalk: Online Learning of Social Representations
- 7. Anomaly Detection in Online Social Network: A Survey
- 8. 論文閱讀：Fake News Detection on Social Media:A Data Mining Perspective
- 9. 【論文筆記 Detection】OHEM: Training Region-based Object Detectors with Online Hard Example Mining
- 10. 論文筆記01 Sign prediction by motif naive bayes model in social networks