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分享式Spam攻击的轻量级检测方案
引用本文:吕少卿,范 丹,张玉清. 分享式Spam攻击的轻量级检测方案[J]. 通信学报, 2015, 36(7): 80-91. DOI: 10.11959/j.issn.1000-436x.2015144
作者姓名:吕少卿  范 丹  张玉清
作者单位:1. 西安电子科技大学 综合业务网理论及关键技术国家重点实验室,陕西 西安710071;2. 中国科学院大学 国家计算机网络入侵防范中心,北京 100190;3. 中国科学院信息工程研究所 信息安全国家重点实验室,北京 100093
基金项目:国家自然科学基金资助项目(61272481);信息安全国家重点实验室开放课题基金资助项目
摘    要:Spam攻击是针对社交网络最主要的攻击方式,分享式Spam攻击具有Spam内容的存储与传播分离的新特性,目前没有有效的检测方案。针对这一问题分析了其攻击过程和特征,利用分享式Spam攻击传播和存储的特征设计了轻量级迭代检测算法LIDA,通过目标筛选和内容检测2个步骤实现对分享式Spam的检测。同时,轻量级算法避免了传统算法对每个用户都做深度检测的问题,更具实用性。通过人人网的4次迭代实验,共检测到9 568个Spam账号、30 732个Spam相册以及2 626 780条Spam URL,表明所提的检测算法对于分享式Spam攻击是行之有效的。

关 键 词:社交网络;分享式Spam;Spam检测;人人网

Lightweight detection system of shared spam attacks
Shao-qing LV,Dan FAN,Yu-qing ZHANG. Lightweight detection system of shared spam attacks[J]. Journal on Communications, 2015, 36(7): 80-91. DOI: 10.11959/j.issn.1000-436x.2015144
Authors:Shao-qing LV  Dan FAN  Yu-qing ZHANG
Affiliation:1. Information Security Research Center of State Key Laboratory of Integrated Services Networks,Xidian University,Xi'an 710071,China;2. National Computer Network Intrusion Protection Center,University of Chinese Academy of Sciences,Beijing 100190,China;3. State Key Laboratory of Information Security Institute of Information Engineering,Chinese Academy of Sciences,Beijing 100093,China
Abstract:Spam is one of the most serious attacks against online social networks (OSN).Recently a new type of spam attack occurs,which named shared spam attack.The shared spam attack can separate the storage and dissemination of spam content,making the existing detection systems no longer effective.To address this problem,an empirical analysis of the process and properties of this new spam attack is performed.A novel lightweight iterative detection algorithm (LIDA) is proposed to detect spam accounts in OSN with these properties.LIDA contains two steps:target filter and content detection.It also noteworthy that LIDA is a lightweight algorithm to infer more spam accounts by exploiting spam accounts’ sharing instead of scanning or analyzing all accounts.Experimental results in RenRen,which has successfully detected 9 568 spam accounts,30 732 spam albums and 2 626 780 spam URL in four round iterations,indicate that LIDA is effective and efficiency in detecting shared spam accounts.
Keywords:online social networks   Spam based on sharing   Spam detection   RenRen
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