[1] WOOD A D, STANKOVIC J A. Denial of Service in Sensor Networks[J]. Computer, 2002, 35(10): 54-62.
[2] ZHANG H, CHENG P, SHI L, et al. Optimal Denial-of-service Attack Scheduling with Energy Constraint[J]. IEEE Transactions on Automatic Control, 2015, 60(11): 3023-3028.
[3] MAHIMKAR A, DANGE J, SHMATIKOV V, et al. Dfence: Transparent Network-based Denial of Service Mitigation[C]//Proceedings of the 4th USENIX Conference on Networked Systems Design & Implementation. Berkeley: USENIX Association, 2007: 24.
[4] 梁洪泉, 吴巍. 利用节点可信度的安全链路状态路由协议[J]. 西安电子科技大学学报, 2016, 43(5): 121-127.
LIANG Hongquanl, WU Wei. Secure Link Status Routing Protocol Based on Node Trustworthiness[J]. Journal of Xidian University, 2016, 43(5): 121-127.
[5] YAN Q, YU F R, GONG Q, et al. Software-defined Networking (SDN) and Distributed Denial of Service (DDoS) Attacks in Cloud Computing Environments: a Survey, Some Research Issues, and Challenges[J]. IEEE Communications Surveys and Tutorials, 2016, 18(1): 602-622.
[6] ZHANG C W, YIN J P, CAI Z P, et al. RRED: Robust RED Algorithm to Counter Low-rate Denial-of-service Attacks[J]. IEEE Communications Letters, 2010, 14(5): 489-491.
[7] BAI Y, XIE C Y, QIN J C. Research of Three-level Detection Algorithm Against Low-rate Denial of Service Attacks[J]. Advanced Materials Research, 2012, 403/404/405/406/407/408: 2325-2328.
[8] ARAVIND B, NARAYANA M L. Detecting Constant Low-frequency Appilication Layer DDOS Attacks Using, Collaborative Algorithms[J]. International Journal of Computer Trends & Technology, 2013, 4(10): 1132-1139.
[9] YU C, KAI H, YU-KWONG K. Collaborative Defense Against Periodic Shrew DDoS Attacks in Frequency Domain[J]. ACM Transactions on Information and System Security, 2005(3): 59-67.
[10] 吴志军, 岳猛. 基于卡尔曼滤波的LDDoS攻击检测方法[J]. 电子学报, 2008, 36(8): 1590-1594.
WU Zhijun, YUE Meng. Detection of LDDoS Attack Based on Kalman Filtering[J]. Acta Electronica Sinica, 2008, 36(8): 1590-1594.
[11] ZHANG X Y, WU Z J, CHEN J S, et al. An Adaptive KPCA Approach for Detecting LDoS Attack[J]. International Journal of Communication Systems, 2017, 30(4): e2993.
[12] WU Z J, JIANG J, YUE M. A Particle Filter-based Approach for Effectively Detecting Low-rate Denial of Service Attacks[C]//Proceedings of the 2016 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery. Piscataway: IEEE, 2017: 86-90.
[13] KANG J, YANG M, ZHANG J Y. Accurately Identifying New QoS Violation Driven by High-distributed Low-rate Denial of Service Attacks Based on Multiple Observed Features[J]. Journal of Sensors, 2015, 2015(2015): 465402.
[14] WU Z J, ZHANG L Y, YUE M. Low-rate DoS Attacks Detection Based on Network Multifractal[J]. IEEE Transactions on Dependable and Secure Computing, 2016, 13(5): 559-567.
[15] AIN A, BHUYAN M H, BHATTACHARYYA D K, et al. Rank Correlation for Low-rate DDoS Attack Detection: an Empirical Evaluation[J]. International Journal of Network Security, 2016, 18(3): 474-480.
[16] SIMSEK M. A New Metric for Flow-level Filtering of Low-rate DDoS Attacks[J]. Security and Communication Networks, 2015, 8(18): 3815-3825.
[17] CORDOVA J, NAVARRO G. Practical Dynamic Entropy-compressed Bitvectors with Applications[C]//Lecture Notes in Computer Science: 9685. Heidelberg: Springer Verlag, 2016: 105-117.
[18] 李青茹. 网络蠕虫的传播模型及其检测技术研究[D]. 西安: 西安电子科技大学, 2016. |