第1期 常利伟，等：基于多源异构数据融合的网络安全态势评估体系 ·47· LIU Xiaowu,WANG Huigiang,LU Hongwu,et al.Fu- data set[J].Information security journal:a global per- sion-based cognitive awareness-control model for network spective,2016,25(1/2/3:18-31 security situation[J].Journal of software,2016,27(8): [18]MOUSTAFA N.SLAY J.CREECH G.Novel geometric 2099-2114 area analysis technique for anomaly detection using [9]WANG Huan,CHEN Zhanfang,FENG Xin,et al.Re- trapezoidal area estimation on large-scale networks[J]. search on network security situation assessment and quan- IEEE transactions on big data,2019,5(4):481-494 tification method based on analytic hierarchy process[J]. [19]MOUSTAFA N,CREECH G,SLAY J.Big data analyt- Wireless personal communications,2018,102(2): ics for intrusion detection system:statistical decision- 1401-1420. making using finite dirichlet mixture models[M].CAR- [10]龚俭，藏小冬，苏琪，等.网络安全态势感知综述.软 RASCOSA I P,KALUTARAGE H K,HUANG Yan. 件学报，2017,28(4：1010-1026 Data Analytics and Decision Support for Cybersecurity. GONG Jian,ZANG Xiaodong,SU Qi,et al.Survey of Cham:Springer,2017:127-156. network security situation awareness[J].Journal of soft- [20]甘文道，周城，宋波.基于RAN-RBF神经网络的网络安 ware,2017,28(4):1010-1026. [11]ZHAO Dongmei,LIU Jinxing.Study on network security 全态势预测模型[J.计算机科学，2016,43(11A): 388-392. situation awareness based on particle swarm optimization algorithm[J.Computers and industrial engineering,2018, GAN Wendao,ZHOU Cheng,SONG Bo.Network secur- 125:764-775. ity situation prediction model based on RAN-RBF neural [12]陈维鹏，敖志刚，郭杰，等.基于改进的BP神经网络的 network[J].Computer science,2016,43(11A):388-392. 网络空间态势感知系统安全评估[J].计算机科学， [21]HECHT-NIELSEN R.Theory of the backpropagation 2018.45(11A):345-347,341 neural network[C]//Proceedings of the International 1989 CHEN Weipeng,AO Zhigang,GUO Jie,et al.Research Joint Conference on Neural Networks.Washington,USA: on cyberspace situation awareness security assessment IEEE,1989:593-605 based on improved BP neural network[J.Computer sci- 作者简介： ence,2018.45(11A:345-347,341. [13]贾焰，韩伟红，杨行.网络安全态势感知研究现状与发 常利伟，副教授，中国计算机学会 展趋势[.广州大学学报（自然科学版），2019,18(3)： 会员、中国密码学会会员、山西省区块 1-10 链研究会理事，主要研究方向为密码 JIA Yan,HAN Weihong,YANG Xing.Summary of net- 算法、网络安全态势感知、量子保密通 信和区块链。参与国家级项目4项， work security situation assessment[J].Journal of Guang- 主持山西省科研及教研项目3项，获 zhou University (natural science edition),2019,18(3): 山西省教学成果一等奖1项。发表学 1-10. [14]XI Rongrong,YUN Xiaochun,HAO Zhiyu.Framework 术论文近20篇。 for risk assessment in cyber situational awareness[J].let 田晓雄，硕士研究生，主要研究方 information security,2019,13(2):149-156. 向为网铬安全和信息融合。 [15]ZHENG Weifa.Research on situation awareness of net- work security assessment based on dempster- shafer[C]//2019 International Conference on Computer Science Communication and Network Security.France: Edition Diffusion Press Sciences,2020:131-136. [16]MOUSTAFA N.SLAY J.UNSW-NB15:a comprehens- ive data set for network intrusion detection systems (UN- 张宇青，硕士研究生，主要研究方 SW-NB15 network data set)[C]//Proceedings of 2015 向为网络安全与模式识别。 Military Communications and Information Systems Con- ference.Canberra,Australia:IEEE,2015:1-6. [17]MOUSTAFA N.SLAY J.The evaluation of network an- omaly detection systems:statistical analysis of the UN- SW-NB15 data set and the comparison with the KDD99LIU Xiaowu, WANG Huiqiang, LU Hongwu, et al. Fu￾sion-based cognitive awareness-control model for network security situation[J]. Journal of software, 2016, 27(8): 2099–2114. WANG Huan, CHEN Zhanfang, FENG Xin, et al. Re￾search on network security situation assessment and quan￾tification method based on analytic hierarchy process[J]. Wireless personal communications, 2018, 102(2): 1401–1420. [9] 龚俭, 臧小冬, 苏琪, 等. 网络安全态势感知综述 [J]. 软 件学报, 2017, 28(4): 1010–1026. GONG Jian, ZANG Xiaodong, SU Qi, et al. Survey of network security situation awareness[J]. Journal of soft￾ware, 2017, 28(4): 1010–1026. [10] ZHAO Dongmei, LIU Jinxing. Study on network security situation awareness based on particle swarm optimization algorithm[J]. Computers and industrial engineering, 2018, 125: 764–775. [11] 陈维鹏, 敖志刚, 郭杰, 等. 基于改进的 BP 神经网络的 网络空间态势感知系统安全评估 [J]. 计算机科学, 2018, 45(11A): 345–347, 341. CHEN Weipeng, AO Zhigang, GUO Jie, et al. Research on cyberspace situation awareness security assessment based on improved BP neural network[J]. Computer sci￾ence, 2018, 45(11A): 345–347, 341. [12] 贾焰, 韩伟红, 杨行. 网络安全态势感知研究现状与发 展趋势 [J]. 广州大学学报(自然科学版), 2019, 18(3): 1–10. JIA Yan, HAN Weihong, YANG Xing. Summary of net￾work security situation assessment[J]. Journal of Guang￾zhou University (natural science edition), 2019, 18(3): 1–10. [13] XI Rongrong, YUN Xiaochun, HAO Zhiyu. Framework for risk assessment in cyber situational awareness[J]. Iet information security, 2019, 13(2): 149–156. [14] ZHENG Weifa. Research on situation awareness of net￾work security assessment based on dempster￾shafer[C]//2019 International Conference on Computer Science Communication and Network Security. France: Edition Diffusion Press Sciences, 2020: 131–136. [15] MOUSTAFA N, SLAY J. UNSW-NB15: a comprehens￾ive data set for network intrusion detection systems (UN￾SW-NB15 network data set)[C]//Proceedings of 2015 Military Communications and Information Systems Con￾ference. Canberra, Australia: IEEE, 2015: 1–6. [16] MOUSTAFA N, SLAY J. The evaluation of network an￾omaly detection systems: statistical analysis of the UN￾SW-NB15 data set and the comparison with the KDD99 [17] data set[J]. Information security journal: a global per￾spective, 2016, 25(1/2/3): 18–31. MOUSTAFA N, SLAY J, CREECH G. Novel geometric area analysis technique for anomaly detection using trapezoidal area estimation on large-scale networks[J]. IEEE transactions on big data, 2019, 5(4): 481–494. [18] MOUSTAFA N, CREECH G, SLAY J. Big data analyt￾ics for intrusion detection system: statistical decision￾making using finite dirichlet mixture models[M]. CAR￾RASCOSA I P, KALUTARAGE H K, HUANG Yan. Data Analytics and Decision Support for Cybersecurity. Cham: Springer, 2017: 127-156. [19] 甘文道, 周城, 宋波. 基于 RAN-RBF 神经网络的网络安 全态势预测模型 [J]. 计算机科学, 2016,43 (11A): 388–392. GAN Wendao, ZHOU Cheng, SONG Bo. Network secur￾ity situation prediction model based on RAN-RBF neural network[J]. Computer science, 2016,43 (11A): 388–392. [20] HECHT-NIELSEN R. Theory of the backpropagation neural network[C]//Proceedings of the International 1989 Joint Conference on Neural Networks. Washington, USA: IEEE, 1989: 593–605. [21] 作者简介： 常利伟，副教授，中国计算机学会 会员、中国密码学会会员、山西省区块 链研究会理事，主要研究方向为密码 算法、网络安全态势感知、量子保密通 信和区块链。参与国家级项目 4 项， 主持山西省科研及教研项目 3 项，获 山西省教学成果一等奖 1 项。发表学 术论文近 20 篇。 田晓雄，硕士研究生，主要研究方 向为网络安全和信息融合。 张宇青，硕士研究生，主要研究方 向为网络安全与模式识别。 第 1 期 常利伟，等：基于多源异构数据融合的网络安全态势评估体系 ·47·