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1. 中国科学院信息工程研究所,北京 100093
2. 中国科学院大学,北京100049
3. 国家计算机应急技术处理协调中心,北京 100029
[ "尹涛(1989-),男,重庆人,中国科学院信息工程研究所博士生,主要研究方向为网络与信息安全。" ]
[ "李世淙(1981-),男,山东临沂人,国家计算机应急技术处理协调中心工程师,主要研究方向为网络安全事件监测、网络行为分析。" ]
[ "庹宇鹏(1984-),男,河北廊坊人,中国科学院信息工程研究所助理研究员,主要研究方向为网络异常检测、移动互联网大数据挖掘。" ]
[ "张永铮(1978-),男,黑龙江哈尔滨人,博士,中国科学院信息工程研究所研究员、博士生导师,主要研究方向为网络安全态势感知。" ]
网络出版日期:2017-01,
纸质出版日期:2017-01-25
移动端阅览
尹涛, 李世淙, 庹宇鹏, 等. 强抗毁性社交僵尸网络的构建及其防御[J]. 通信学报, 2017,38(1):97-105.
Tao YIN, Shi-cong LI, Yu-peng TUO, et al. Modeling and countermeasures of a social network-based botnet with strong destroy-resistance[J]. Journal on communications, 2017, 38(1): 97-105.
尹涛, 李世淙, 庹宇鹏, 等. 强抗毁性社交僵尸网络的构建及其防御[J]. 通信学报, 2017,38(1):97-105. DOI: 10.11959/j.issn.1000-436x.2017012.
Tao YIN, Shi-cong LI, Yu-peng TUO, et al. Modeling and countermeasures of a social network-based botnet with strong destroy-resistance[J]. Journal on communications, 2017, 38(1): 97-105. DOI: 10.11959/j.issn.1000-436x.2017012.
为打击僵尸网络,保障网络空间安全,提出一种新型的具备强抗毁性的社交僵尸网络(DR-SNbot),并给出了针对性的防御方法。DR-SNbot 基于社交网络搭建命令与控制服务器(C&C-Server
command and control server),每个 C&C-Server 对应一个不同的伪随机昵称,并利用信息隐藏技术将命令隐藏在日志中发布,进而提出一种新型的命令与控制信道。当C&C-Server不同比例地失效时,DR-SNbot会发出不同等级的预警,通知攻击者构建新的C&C-Server,并自动修复C&C通信以保障其强抗毁性。在实验环境中,即使当前C&C-Server全部失效,DR-SNbot仍能在短期内修复C&C通信,将控制率维持在100%。最后,基于伪随机僵尸昵称与合法昵称在词法特征上的差异性,提出一种僵尸昵称检测方法,可有效检测社交僵尸网络利用自定义算法批量生成的伪随机僵尸昵称。实验结果表明,该方法召回率达到93%,准确率达到96.88%。
To defeat botnets and ensure cyberspace security
a novel social network-based botnet with strong destroy-resistance (DR-SNbot)
as well as its corresponding countermeasure
was proposed.DR-SNbot constructed command and control servers (C&C-Servers) based on social network.Each C&C-Server corresponded to a unique pseudo-random nickname.The botmaster issues commanded by hiding them in diaries using information hiding techniques
and then a novel C&C channel was established.When different proportions of C&C-Servers were invalid
DR-SNbot would send out different levels of alarms to inform attackers to construct new C&C-Servers.Then
DR-SNbot could automatically repair C&C communication to ensure its strong destroy-resistance.Under the experimental settings
DR-SNbot could resume the C&C communication in a short period of time to keep 100% of the control rate even if all the current C&C-Servers were invalid.Finally
a botnet nickname detecting method was proposed based on the difference of lexical features of legal nicknames and pseudo-random nicknames.Experimental results show that the proposed method can effectively (precision:96.88%
recall:93%) detect pseudo-random nicknames generated by social network-based botnets with customized algorithms.
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