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[ "俞艺涵(1992-),男,海军工程大学信息安全系硕士生,主要研究方向为信息系统安全。" ]
[ "付钰(1982-),女,博士,海军工程大学信息安全系副教授,主要研究方向为信息安全风险评估。" ]
[ "吴晓平(1961-),男,博士,海军工程大学信息安全系教授,主要研究方向为系统分析与决策。" ]
[ "李洪成(1991-),男,海军工程大学信息安全系博士生,主要研究方向为大数据安全与风险评估。" ]
网络出版日期:2016-01,
纸质出版日期:2016-01-20
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俞艺涵, 付钰, 吴晓平, 等. 一种基于同源行为分析的APT异常发现策略[J]. 电信科学, 2016,32(1):82-87.
Yihan YU, Yu FU, Xiaoping WU, et al. A discovery strategy for APT anomaly based on homologous behavior analysis[J]. Telecommunications science, 2016, 32(1): 82-87.
俞艺涵, 付钰, 吴晓平, 等. 一种基于同源行为分析的APT异常发现策略[J]. 电信科学, 2016,32(1):82-87. DOI: 10.11959/j.issn.1000-0801.2016012.
Yihan YU, Yu FU, Xiaoping WU, et al. A discovery strategy for APT anomaly based on homologous behavior analysis[J]. Telecommunications science, 2016, 32(1): 82-87. DOI: 10.11959/j.issn.1000-0801.2016012.
APT(advanced persistent threat)攻击的日益频繁对APT攻击行为的检测提出了更高的要求,对同源行为进行分析是尽早发现APT攻击行为的一种有效方法。针对数据量过大造成数据对比认证效率低下的难题,提出了借助数据标签技术,建立历史同源行为数据库,并将数据库存储到云端;依托Hadoop平台和MapReduce聚合计算能力,基于伪随机置换技术完成网络全流量并行检测,通过与数据库中的数据标签进行对比验证,来判断是否有APT攻击行为。测试结果表明,该方法可尽早从网络中发现APT异常行为,提高全数据流检测的效率。
As APT(advanced persistent threat)attacks are increasingly frequently
higher requirements for the detection of APT attacks were proposed.It was an effective method to early discover the attack behavior of APT based on homologous behavior analysis.Aiming at the problem of low efficiency of data authentication caused by excessive data
the historical behavior database with data label technology was established and the database was stored in the cloud.Relying on the Hadoop platform and the aggregate computing ability of MapReduce and the pseudorandom permutation technique
the whole traffic parallel detection of the network was realized.In order to determine whether there was a APT attack behavior
the detection of APT attacks was implemented by comparing the data labels in the database.Test results show that the proposed method can detect the abnormal behavior of APT from the network as soon as possibleand improve the efficiency of the whole data flow detection.
CHEN P , DESMET L , HUYGENS C . A study on advanced persistent threats [C ] // Proceedings of the 15th International Conference Conference on Communications and Multimedia Security , September 25 - 26 , 2014 , Aveiro,Portugal . Berlin : Springer Press , 2014 : 56 - 73 .
NIKOS V , DIMITRI G . The big four-what we did wrong in advanced persistent threat detection [C ] // Proceedings of International Conference on Availability,Reliability and Security , September 2 - 6 , 2013 , Washington DC,USA . New Jersey : IEEE Press , 2013 : 248 - 254 .
YANG G M Z , TIAN Z H , DUAN W L . The prevent of advanced persistent threat [J ] . Journal of Chemical and Pharmaceutical Research , 2015 , 6 ( 1 ): 572 - 576 .
杜跃进 , 翟立东 , 李跃 , 等 . 一种应对APT 攻击的安全架构:异常发现 [J ] . 计算机研究与发展 , 2014 , 7 ( 7 ): 1633 - 1645 .
DU Y J , ZHAI L D , LI Y , et al . Security architecture to deal with APT attacks:abnormal discovery [J ] . Journal of Computer Research and Development , 2014 , 7 ( 7 ): 1633 - 1645 .
李凤海 , 李爽 , 张佰龙 , 等 . 高等级安全网络抗APT攻击方案研究 [J ] . 信息网络安全 , 2014 ( 9 ): 109 - 114 .
LI F H , LI S , ZHANG B L , et al . An anti-APT scheme research for high-security network [J ] . Netinfo Security , 2014 ( 9 ): 109 - 114 .
COLE E . Advanced Persistent Threat:Understanding the Danger and How to Protect Your Organization [M ] . Boca Raton : CRC Press , 2012 : 1 - 280 .
郑黎明 , 邹鹏 , 贾焰 , 等 . 网络流量异常检测中分类器的提取与训练方法研究 [J ] . 计算机学报 , 2012 ( 4 ): 719 - 729 .
ZHENG L M , ZOU P , JIA Y , et al . How to extract and train the classifier in traffic anomaly detection system [J ] . Chinese Journal of Computers , 2012 ( 4 ): 719 - 729 .
许婷 . 一种有效防范APT攻击的网络安全架构 [J ] . 信息安全与通信保密 , 2013 ( 6 ): 65 - 67 .
XU T . A hierarchical-centralized network security architecture effectively preventing APT attacks [J ] . China Information Security , 2012 ( 4 ): 65 - 67 .
SEJONG O , SEOG P . Task-role-based access control model [J ] . Information System , 2003 ( 28 ): 533 - 562 .
张鸽 . 基于网络行为分析的跨站攻防技术的研究 [D ] . 郑州 : 解放军信息工程大学 , 2012 : 46 .
ZHANG G . Analysis of offensive and defensive techniques cross station based on network behavior [D ] . Zhengzhou : PLA Information Engineering University , 2012 : 46 .
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