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实验室科研成果列表(2022.06)

已有 1450 次阅读 2022-6-29 00:11 |个人分类:1_实验室综述|系统分类:科研笔记

实验室近年科研成果(论文)

(截止2022.06

一、 论文代表作

1)      Dan Tang, Yudong Yan*, Siqi Zhang, Jingwen Chen, Zheng Qin. Performance and Features: Mitigating the Low-Rate TCP-targeted DoS Attack via SDN. IEEE Journal on Selected Areas in Communications,  2022, 40(1)428-444. CCF-A, SCI一区)

DOI: https://doi.org/10.1109/JSAC.2021.3126053


2)      Dan Tang, Xiyin Wang, Xiong Li, Pandi Vijayakumar, and Neeraj Kumar*. AKN-FGD: Adaptive Kohonen Network based Fine-grained Detection of LDoS Attack. IEEE Transactions on Dependable and Secure Computing, 2021, ( Early Access ).  CCF-A, SCI二区)

DOI: https://doi.org/10.1109/TDSC.2021.3131531


3)      Dan Tang, Siqi Zhang *, Yudong Yan, Jing-Wen Chen, Zheng Qin. Real-time Detection and Mitigation of LDoS Attacks in the SDN Using the HGB-FP Algorithm. IEEE Transactions on Services Computing2021, ( Early Access ). CCF-B, SCI二区)

DOI: https://doi.org/10.1109/TSC.2021.3102046


4)      Dan Tang, Ye Feng*, Siqi Zhang, Zheng Qin. FR-RED: Fractal Residual based Real-time Detection of the LDoS Attack. IEEE Transactions on Reliability. 2021, 70 (3), 1143-1157. SCI三区)

DOI: https://doi.org/10.1109/TR.2020.3023257


5)      Dan Tang, Siqi Zhang*, Xi-Yin Wang, Jing-Wen Chen. The Detection of Low-rate DoS Attack Using SADBSCAN Algorithm. Information Sciences, 2021, vol 565, 229-247. CCF-B, SCI二区)

DOI: https://doi.org/10.1016/j.ins.2021.02.038


6)      Dan Tang, Liu Tang, Rui Dai, Jingwen Chen, Xiong Li, Joel J.-P. C. Rodrigues*MF-Adaboost: LDoS attack detection based on multi-features and improved Adaboost. Future Generation Computer Systems. 2020, vol 106, 347-359. CCF-C,  SCI二区)

DOI: http://dx.doi.org/10.1016/j.future.2019.12.034 


7)      Dan Tang, Jingwen Chen, Xiyin Wang, Siqi Zhang, Yudong Yan. A New Detection Method for LDoS Attacks based on Data Mining. Future Generation Computer Systems,2022, vol 128, 73-87. CCF-C, SCI二区)

DOI: https://doi.org/10.1016/j.future.2021.09.039


8)      Dan Tang, Jianping Man*, Liu Tang, Ye Feng, Qiuwei Yang. WEDMS: An Advanced Mean Shift Clustering Algorithm for LDoS Attacks Detection. Ad Hoc Networks, 2020, vol 102, 102145. CCF-C, SCI二区)

DOI: https://doi.org/10.1016/j.adhoc.2020.102145 


9)      Wei Shi*, Dan Tang, Sijia Zhan, Zheng Qin, Xiyin Wang. An approach for detecting LDoS attack based on cloud model. Frontiers of Computer Science, 2022, vol 16, 166821. CCF-C, SCI二区)

DOI: https://doi.org/10.1007/s11704-022-0486-1

 

二、 近年所有科研论文

2022年(4篇)

1Dan Tang, Yudong Yan*, Siqi Zhang, Jingwen Chen, Zheng Qin. Performance and Features: Mitigating the Low-Rate TCP-targeted DoS Attack via SDN. IEEE Journal on Selected Areas in Communications,  2022, 40(1)428-444. CCF-A, SCI一区)

DOI: https://doi.org/10.1109/JSAC.2021.3126053


2Dan Tang, Jingwen Chen, Xiyin Wang, Siqi Zhang, Yudong Yan. A New Detection Method for LDoS Attacks based on Data Mining. Future Generation Computer Systems,2022, vol 128, 73-87. CCF-C, SCI二区)

DOI: https://doi.org/10.1016/j.future.2021.09.039 


3Wei Shi*, Dan Tang, Sijia Zhan, Zheng Qin, Xiyin Wang. An approach for detecting LDoS attack based on cloud model. Frontiers of Computer Science, 2022, vol 16, 166821. CCF-C, SCI二区)

DOI: https://doi.org/10.1007/s11704-022-0486-1


4Dan Tang, Xiyin Wang, Yudong Yan, Dongshuo Zhang, Huan Zhao. ADMS: An online attack detection and mitigation system for LDoS attacks via SDN, Computer Communications, 2022, 181454-471. CCF-C, SCI三区)

DOI: https://doi.org/10.1016/j.comcom.2021.10.007


2021年(10篇)

1)      Dan Tang, Xiyin Wang, Xiong Li, Pandi Vijayakumar, and Neeraj Kumar*. AKN-FGD: Adaptive Kohonen Network based Fine-grained Detection of LDoS Attack. IEEE Transactions on Dependable and Secure Computing, 2021, ( Early Access ). CCF-A, SCI二区)

DOI: https://doi.org/10.1109/TDSC.2021.3131531


2)      Dan Tang, Siqi Zhang *, Yudong Yan, Jing-Wen Chen, Zheng Qin. Real-time Detection and Mitigation of LDoS Attacks in the SDN Using the HGB-FP Algorithm. IEEE Transactions on Services Computing. 2021, ( Early Access ). CCF-B, SCI二区)

DOI: https://doi.org/10.1109/TSC.2021.3102046


3)      Dan Tang, Siqi Zhang*, Xi-Yin Wang, Jing-Wen Chen. The Detection of Low-rate DoS Attack Using SADBSCAN Algorithm. Information Sciences, 2021, vol 565, 229-247. CCF-B, SCI二区)

DOI: https://doi.org/10.1016/j.ins.2021.02.038


4)      Dan Tang, Ye Feng*, Siqi Zhang, Zheng Qin. FR-RED: Fractal Residual based Real-time Detection of the LDoS Attack. IEEE Transactions on Reliability.  2021, 70 (3), 1143-1157. SCI三区)

DOI: https://doi.org/10.1109/TR.2020.3023257


5Dan Tang , Liu Tang* , Wei Shi , Sijia Zhan , Qiuwei Yang. MF-CNN: A New Approach for LDoS Attack Detection Based on Multi-feature Fusion and CNN. Mobile Networks and Applications, 2021, 26(4)1705-1722.  CCF-C, SCI三区)

DOI: https://doi.org/10.1007/s11036-019-01506-1


6Dan Tang, Dongshuo Zhang*, Huan Zhao, Dashun Liu, Yudong Yan, Jingwen Chen. Network Attack Detection Towards Smart Factory. The 27th IEEE Real-Time and Embedded Technology and Applications SymposiumRTAS 2021,  2021: 485-488. CCF-B会)

DOI: https://doi.org/10.1109/RTAS52030.2021.00058


7Siyuan Wang, Dan Tang*, Yu Liu, Rui Dai, Jingwen Chen.  LDoS Attack Detection Using PSO and K-means Algorithm. International Conference on Computer Supported Cooperative Work in DesignCSCWD 2021, 2021, 317-322. CCF-C会)

DOI: https://doi.org/10.1109/CSCWD49262.2021.9437702


8Xinmeng Li, Kai Zheng, Dan Tang*, Zheng Qin, Zhiqing Zheng , Shihan Zhang . LDoS Attack Detection Based on ASNNC-OFA Algorithm. The 2021 IEEE Wireless Communications and Networking ConferenceWCNC 2021, 2021, 1-6. CCF-C会) 

DOI: https://doi.org/10.1109/WCNC49053.2021.9417400


9Boru Liu, Dan Tang*, Yudong Yan, Zhiqing Zheng, Shihan Zhang, Jiangmeng Zhou. TS-SVM: Detect LDoS Attack in SDN Based on Two-step Self-adjusting SVM. The 20th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2021), 2021: 678-685.CCF-C会)

DOI:https://doi.org/10.1109/TrustCom53373.2021.00100


10Xinmeng Li, Nengguang Luo, Dan Tang*, Zhiqing Zheng, Zheng Qin and Xinxiang Gao.BA-BNN: Detect LDoS Attacks in SDN Based on Bat Algorithm and BP Neural Network. The 19th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA 2021), 2021, 300-307. CCF-C会)

DOI:https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom52081.2021.00050


2020年(6篇)

1Dan Tang, Liu Tang, Rui Dai, Jingwen Chen, Xiong Li, Joel J.-P. C. Rodrigues*MF-Adaboost: LDoS attack detection based on multi-features and improved Adaboost. Future Generation Computer Systems. 2020, vol 106, 347-359. CCF-C,  SCI二区)

DOI: http://dx.doi.org/10.1016/j.future.2019.12.034 


2Dan Tang, Jianping Man*, Liu Tang, Ye Feng, Qiuwei Yang. WEDMS: An Advanced Mean Shift Clustering Algorithm for LDoS Attacks Detection. Ad Hoc Networks, 2020, vol 102, 102145.CCF-C, SCI二区)

DOI: https://doi.org/10.1016/j.adhoc.2020.102145 


3Dan Tang, Rui Dai*, Liu Tang, XiongLi. Low-rate DoS attack detection based on two-step cluster analysis and UTR analysis. Human-centric Computing and Information Sciences, 2020, 10(1):6.(SCI 三区)

DOI: https://doi.org/10.1186/s13673-020-0210-9 


4Sijia Zhan, Dan Tang*, Jianping Man, Rui Dai, Xiyin Wang. Low-Rate DoS Attacks Detection Based on MAF-ADM. Sensors, 2020, 20(1), 189. SCI三区)

DOI: https://doi.org/10.3390/s20010189 


5Zhiqing Zheng, Dan Tang*, Siyuan Wang, Xiaoxue Wu, Jingwen Chen.  An Efficient Detection Approach for LDoS attack based on NCS-SVM Algorithm. The 29th International Conference on Computer Communications and NetworksICCCN 2020, 2020, pp. 1-9. CCF-C类)

DOI: https://doi.org/10.1109/ICCCN49398.2020.9209699


6Xiaocai Wang, Qiuwei Yang, Zichao Xie, Zhiqing Zheng, Yudong Yan, Dan Tang*.  Low-rate DoS Attack Detection Based on WPD-EE Algorithm. The 18th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA 2020), 2020; 384-391CCF-C类)

DOI: https://doi.org/10.1109/ISPA-BDCloud-SocialCom-ustainCom51426.2020.00074


2018-2019年(4篇)

1Dongshuo Zhang, Dan Tang*, Liu Tang , Rui Dai, Jingwen Chen Ningbo Zhu. PCA-SVM-Based Approach of Detecting Low-Rate DoS Attack. In 2019 IEEE 21st International Conference on High Performance Computing and Communications (HPCC). IEEE, 2019: 1163-1170.  CCF-C会)

DOI: https://doi.org/10.1109/HPCC/SmartCity/DSS.2019.00164


2Yudong Yan, Dan Tang*, Sijia Zhan, Rui Dai, Jingwen Chen. Low-Rate DoS Attack Detection Based on Improved Logistic Regression. In IEEE 21st International Conference on High Performance Computing and CommunicationsHPCC2019: 468-476. CCF-C会)

DOI: https://doi.org/10.1109/HPCC/SmartCity/DSS.2019.00076


3Dan Tang, Rui Dai*, Liu Tang, Sijia Zhan, and Jianping Man. Low-Rate DoS Attack Detection Based on Two-Step Cluster Analysis. In International Conference on Information and Communications SecurityICICS, 2018; 92-104. CCF -C会)

DOI:https://doi.org/10.1007/978-3-030-01950-1_6


4Xiaoxue Wu, Dan Tang*, Liu Tang, Jianping Man, Sijia Zhan and Qin Liu. A Low-Rate DoS Attack Detection Method Based on Hilbert Spectrum and Correlation. In 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), 2018; 1358-1363. CCF -C会)

DOI: https://doi.org/10.1109/SmartWorld.2018.00236


在审论文(12篇)

1Dan Tang, Jianping Man*, Ye Feng, Wei Shi, Siqi Zhang, Zheng Qin. MFOPA-Based Detection of Low-Rate DoS Attacks. Mobile Networks & Applications, under reviewCCF-C, SCI三区)

2Dan Tang, Jingwen Chen*, Siqi Zhang, Xiyin Wang. LDoS Attack Detection Model Based on KMFCM Algorithm. Journal of Systems and Software, under review. CCF-B, SCI三区)

3Tang D, Wang Xiyin*, Li Xiong, Vijayakumar P, Kumar, Neeraj. AdaKcn: An Efficient Scheme for LDoS Attack Detection in Heterogeneous Networks. IEEE Transactions on Network Science and Engineering, under review.

4Dan Tang, Wei Shi*, Ye Feng, Jingwen Chen, Zheng Qin. MC-HSF:Low-Rate DoS Attacks Detection using Half-Space Forest Algorithm Based on Mel Cepstrum. Journal of Network and Computer Applications, under review. CCF-B, SCI二区)

5Dan Tang, Ye Feng*, Sijia Zhan and Xiyin Wang. An Approach for Detecting LDoS Attack based on Cloud Model. IEEE Transactions on Network and Service Management, under review.CCF-B, SCI二区)

6Dan Tang, Xiyin Wang*. ADMS:An Online Attack Detection and Mitigation System for LDoS Attacks on SDN Controllers. IEEE Conference on Computer Communications.CCF-A类)

7Dan Tang, Siqi Zhang*. Real-time Detection and Mitigation of LDoS Attacks in SDN Using HGB-FP Algorithm. IEEE Transactions on Services Computing, under review.SCI二区)

8Dan Tang, Jingwen Chen*. Online Anomaly Detection and Mitigation Model for LDoS Attacks in Software-Defined Networking. IEEE Transactions on Network and Service Management, under review. SCI二区)

9Dan Tang, Yudong Yan*. Performance and Features: Lightweight SDN Framework for LDoS Attack Detection and Defense. IEEE Conference on Computer Communications.CCF-A类)

10Dan Tang, Rui Dai*. A Novel LDoS attack Detection Method Based on Reconstruction Anormaly. International Conference on Dependable Systems and Networks, under review. CCF-B类)

11Dan Tang, Xiyin Wang*. ShrewGuard: Real-time Detection and Mitigation System of LDoS Attacks in SDN. Future Generation Computer Systems, under review. CCF-B类).





实验室近年科研成果(专利软著)

(截止2022.06

一、近年专利

授权专利(12项)

1)汤澹; 代锐; 唐柳等, 一种基于两步聚类和检测片分析联合算法的LDoS检测方法, 授权公告日:20201027, 中国, ZL201810820413.2.

2)汤澹; 满坚平; 代锐等, 一种基于WEDMS聚类的慢速拒绝服务攻击检测方法, 授权公告日:20210601, 中国, ZL201910004190.7.

3)汤澹; 满坚平; 代锐等, 一种基于MFOPA算法的慢速拒绝服务攻击检测方法, 授权公告日:20210727, 中国, ZL202010406379.1.

4)汤澹; 冯叶; 张斯琦等, 一种基于分形残差的LDoS攻击实时检测方法, 授权公告日:20210727, 中国, ZL202010183854.3.

5)汤澹; 严裕东; 王曦茵等, 一种基于P-F的软件定义网络慢速拒绝服务攻击检测方法, 授权公告日:20210727, 中国, ZL202011068857.9.

6)汤澹; 王思苑; 刘宇等, 一种基于PSO-K算法的LDoS攻击检测方法, 授权公告日:20220125, 中国, ZL202011022723.3.

7)汤澹; 张冬朔; 代锐等, 一种基于频域特征融合的LDoS攻击检测方法, 授权公告日:20220201, 中国, ZL202110120506.6.

8)汤澹; 陈静文; 王曦茵等, SDN中基于ET-EDRLDoS攻击检测与缓解方法, 授权公告日:20220301, 中国, ZL202110130818.5.

9)汤澹; 张冬朔; 王曦茵等, 基于RF-GMMSDNLDoS攻击检测方法, 授权公告日:20220301, 中国, ZL202110130841.4.

10)汤澹; 张斯琦; 陈静文等, 基于集成学习和寻峰算法的LDoS攻击检测与缓解方法, 授权公告日:20220513, 中国, ZL202110130808.1.

11)汤澹; 王曦茵; 张斯琦等, SDN中基于FGD-FMLDoS攻击检测与缓解方法, 授权公告日:20220513, 中国, ZL202110129267.0.

12)汤澹; 张斯琦; 王曦茵等, 基于流量系数的低速DoS攻击实时响应方法, 办理登记手续, 中国, ZL202111323570.0.

 

实审专利(22项)

1)      汤澹; 陈夏润; 张聪聪等,一种基于AEWMA算法的慢速拒绝服务攻击检测方法,中国, CN201710196791.3,实审中。

2)       汤澹; 冯叶; 詹思佳等, 一种基于流量频数分布特征的LDoS快速检测方法, 2018-7-24, 中国, CN201810818118.3,实审中。

3)      汤澹; 施玮; 满坚平等, 一种针对慢速拒绝服务攻击的综合检测方法, 2018-7-24, 中国, CN201810820673.X,实审中。

4)       汤澹; 詹思佳; 施玮等, 一种基于云模型的低速拒绝服务攻击检测方法, 2019-1-3, 中国, CN201910004346.1,实审中。

5)      汤澹; 唐柳; 冯叶等, 一种基于多特征融合和CNN算法的LDoS攻击检测方法, 2019-1-3, 中国, CN201910004666.7,实审中。

6)      汤澹; 郑凯; 罗能光等, 一种基于SNN-LOF算法的慢速拒绝服务攻击检测方法, 2019-1-3, 中国, CN201910004189.4,实审中。

7)      汤澹; 陈静文; 施玮等, 一种基于FCM算法的慢速拒绝服务攻击检测方法, 2019-9-26, 中国, CN201910914381.7,实审中。

8)      汤澹; 张斯琦; 代锐等, 一种基于SA-DBSCAN算法的低速率拒绝服务攻击检测方法, 2019-9-26, 中国, CN201910920919.5,实审中。

9)      汤澹; 严裕东; 冯叶等, 一种基于LR算法的慢速拒绝服务攻击检测方法, 2019-9-27, 中国, CN201910920763.0,实审中。

10)  汤澹; 张冬朔; 代锐等, 一种基于PCA-SVM算法的慢速拒绝服务攻击检测方法, 2019-9-27, 中国, CN201910920902.X,实审中。

11)  汤澹; 陈藜文; 施玮等, 一种基于Elman神经网络的低速率拒绝服务攻击检测方法, 2019-9-27, 中国, CN201910920718.5,实审中。

12)  汤澹; 施玮; 王曦茵等, 一种基于梅尔倒谱与半空间森林结合的LDoS攻击检测方法, 2020-3-16, 中国, CN202010183134.7,实审中。

13)  汤澹; 王曦茵; 冯叶等, 一种基于AKN算法的慢速拒绝服务攻击检测方法, 2020-3-18, 中国, CN202010190244.6,实审中。

14)  冯叶; 詹思佳; 汤澹等, 一种基于MAF-ADM的低速率拒绝服务攻击检测方法, 2020-5-14, 中国, CN202010406757.6,实审中。

15)  施玮; 唐柳; 汤澹等, 一种基于MF-Ada算法的LDoS攻击检测方法, 2020-5-14, 中国, CN202010406743.4,实审中。

16)  汤澹; 郑芷青; 严裕东等, 一种基于NCS-SVMLDoS攻击检测方法, 2020-9-24, 中国, CN202011015908.1,实审中。

17)  汤澹; 张斯琦; 代锐等, 一种基于TC-UTR算法的慢速拒绝服务攻击检测方法, 2020-9-28, 中国, CN202011054835.7,实审中。

18)  汤澹; 严裕东; 冯叶等, 一种基于FSWT时频分布的LDoS攻击检测方法, 2021-1-28, 中国, CN202110119625.X,实审中。

19)  汤澹; 王曦茵; 施玮等, 一种基于SDN控制器的LDoS攻击检测与缓解方案, 2021-1-28, 中国, CN202110121874.2,实审中。

20)  汤澹; 陈静文; 吴小雪等, 一种基于HSS算法的慢速拒绝服务攻击检测方法, 2021-1-29, 中国, CN202110129487.3,实审中。

21)  汤澹; 李欣萌; 王思苑等, 一种基于BA-BNN算法的LDoS攻击检测方法, 2021-7-16, 中国, CN202110809191.6,实审中。

22)  汤澹; 刘泊儒; 郑芷青等, 基于两步自调节支持向量机的LDoS攻击检测方法, 2021-7-16, 中国, CN202110809194.X,实审中。

 

二、软著

1)汤澹,张冬朔,唐柳等,基于PCA-SVM算法的网络攻击检测系统,登记号:2019SR0989748

2)汤澹,张斯琦,王曦茵等,基于DBSCAN算法的网络攻击检测系统,登记号:2019SR0989741

3)汤澹,陈藜文,王曦茵等,基于Elman神经网络的网络攻击检测系统,登记号:2019SR0990036

4)汤澹,陈静文,王曦茵等,基于改进FCM算法的网络攻击检测系统,登记号:2019SR0981700

5)汤澹, 严裕东,詹思佳等,基于改进逻辑回归的网络攻击检测系统,登记号:2019SR0778126

6)汤澹,唐柳,詹思佳等,基于Adaboost算法的网络攻击检测系统,登记号:2019SR0778120

7)汤澹,王曦茵,张斯琦等,基于优化KNMMD聚类算法的网络攻击检测系统,登记号:2019SR0778115

8)汤澹,满坚平,詹思佳等,基于WEDMS聚类算法的网络流量监测系统,登记号:2019SR0223483

9)汤澹,郑凯,唐柳等,基于SNN密度聚类的网络攻击检测系统,登记号:2019SR0223483

10)汤澹,詹思佳,郑凯等,基于云模型的网络攻击检测系统,登记号:2019SR0223359

11)汤澹,代锐,冯叶等,基于两步聚类分析和UTR分析的攻击检测系统,登记号:2019SR0223350

12)汤澹,吴小雪,陈静文等,基于HHTPearson相关的攻击检测系统,登记号:2019SR0223359

13)汤澹,林国龙,赖明曦等,基于自动语音识别的监控视频筛选系统,登记号:2019SR0218850

14)汤澹,冯叶,施玮等,基于卡尔曼滤波的网络攻击检测系统,登记号:2019SR0360123

15)汤澹,施玮,代锐等,基于Kernel算法的攻击流量分析系统,登记号:2019SR0360110

16)汤澹,唐柳,陈静文等,基于深度学习CNN网络的攻击检测系统,登记号:2019SR0369699






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