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| Author: |
戴君翰 Jyun-han Dai |
|---|---|
| Thesis Title: |
基於粉絲頁成長行為時間序列模型之社群網路點擊綁架偵測機制 Detecting Clickjacking on Social Network Through Time-evolution of Fanpage Growing Behavior Modeling |
| Advisor: |
李漢銘
Hahn-Ming Lee |
| Committee: |
林豐澤
Feng-tse Lin 鄭博仁 Albert B. Jeng 廖弘源 Mark Liao 鄭欣明 Shin-ming Cheng |
| Degree: |
碩士 Master |
| Department: |
電資學院 - 資訊工程系 Department of Computer Science and Information Engineering |
| Thesis Publication Year: | 2014 |
| Graduation Academic Year: | 102 |
| Language: | 英文 |
| Pages: | 74 |
| Keywords (in Chinese): | 社群網路 、點擊綁架 、馬可夫模型 、相似度 |
| Keywords (in other languages): | Social network, Clickjacking, Markov model, Similarity measure |
| Reference times: | Clicks: 488 Downloads: 3 |
| Share: |
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隨著的社群網路服務日漸發達,社群網路上的惡意攻擊行為越來越多樣化。 惡意點擊綁架是個傳統的網頁攻擊手法,但是透過結合社群網路,發展出一個新興的攻擊手法。社群網路服務提供商(如:Facebook)迫切需要一套惡意點 擊綁架粉絲頁的防禦或偵測機制。然而,傳統的惡意點擊保護或偵測機制都以客戶端實作為主。社群服務提供商無法強致使用者安裝保護機制。並且在近年來的研究指出,現今的惡意點擊綁架保護與偵測機制都有機會被破解。本研究提出利用粉絲頁中粉絲成長行為之時間序列分析,偵測 Facebook 上的惡意點擊綁架粉絲頁。
The service providers of social network urgently require the confrontation through the modeling the ”clickjacking” patterns to detect the Clickjacking fans pages behavior.The Clikjacking in social network is bypassed currently not only signature-based mechanisms but also more complicated abnormal patterns, e.g., bipartite relations between users and pages. Therefore, in this study, we pro- pose a mechanisms named Clickjacking Hunter, detect Clickjacking fanpages throuhgh modeling fans base growing of fanpages evolution.
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