research-article

Performance Analysis of Mimic Defense based SDN Security Policy

Authors:

Youjun BuAuthors Info & Claims

ICCIR '22: Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics

Pages 7 - 12

https://doi.org/10.1145/3548608.3561128

Published: 14 October 2022 Publication History

Abstract

With the rapid popularization and development of computers and mobile devices, the corresponding modern network devices and network structures have become more advanced and more complex. SDN has the advantages of centralized control, open interface, network virtualiza-tion, etc. and has been applied in various modern network management. However, because the SDN network has the characteristics of central-ized control, the SDN controller will also become a key target of the attack. This article combines mimic defense with SDN technology, focus-es on quantitative analysis of mimic defense in SDN applications, the impact of different defense strategies on the security of the entire system, shows the influence of different conditions on system security, and solves the optimal configuration policy. Finally, experiments are performed to demonstrate the effectiveness of different mimicry defense strategies, which confirms our theoretical strategies.

References

[1]

Mehdi Bahrami. 2015. Cloud Computing for Emerging Mobile Cloud Apps. In 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2015, San Francisco, CA, USA, March 30 - April 3, 2015, 4–5. https://doi.org/10.1109/MobileCloud.2015.40

Digital Library

[2]

David S Linthicum. 2017. Connecting Fog and Cloud Computing. IEEE Cloud Comput. 4, 2: 18–20. https://doi.org/10.1109/MCC.2017.37

[3]

Malhotra, Shweta, Doja, Mohammad Najmud, Alam, Bashir and Alam, Mansaf. 2017. Bigdata analysis and comparison of bigdata analytic approch-es. In International Conference on Computing, 309–314.

[4]

Dingde Jiang, Yuqing Wang, Zhihan Lv, Sheng Qi, and Surjit Singh. 2020. Big Data Analysis Based Network Behav-ior Insight of Cellular Networks for Industry 4.0 Applications. IEEE Trans. Ind. Informatics 16, 2: 1310–1320. https://doi.org/10.1109/TII.2019.2930226

[5]

Nagpal, Chetna, Upadhyay, Prabhat Kumar, Hussain, Syed Shahzeb, Bimal, Annanya Chowdhury and Jain, Shubham. 2019. IIoT Based Smart Factory 4.0 over the Cloud. In 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE).

[6]

Dingde Jiang, Yuqing Wang, Zhihan Lv, Wenjuan Wang, and Huihui Wang. 2020. An Energy-Efficient Networking Approach in Cloud Services for IIoT Networks. IEEE J. Sel. Areas Commun. 38, 5: 928–941. https://doi.org/10.1109/JSAC.2020.2980919

[7]

Gupta, Alok Kumar and Johari, Rahul. 2019. IOT based Electrical Device Surveillance and Control System. In 2019 4th Interna-tional Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU).

[8]

Dong-Hwan Park, Hyo-Chan Bang, Cheol Sik Pyo, and Soon-Ju Kang. 2014. Semantic open IoT service platform technology. In IEEE World Forum on Internet of Things, WF-IoT 2014, Seoul, South Korea, March 6-8, 2014, 85–88. https://doi.org/10.1109/WF-IoT.2014.6803125

[9]

Mohammad Abu-Matar and Rabeb Mizouni. 2018. Variability Modeling for Smart City Reference Architectures. In IEEE International Smart Cities Conference, ISC2 2018, Kansas City, MO, USA, September 16-19, 2018, 1–8. https://doi.org/10.1109/ISC2.2018.8656967

[10]

Dingde Jiang, Peng Zhang, Zhihan Lv, and Houbing Song. 2016. Energy-Efficient Multi-Constraint Routing Algo-rithm With Load Balancing for Smart City Applications. IEEE Internet Things J. 3, 6: 1437–1447. https://doi.org/10.1109/JIOT.2016.2613111

[11]

Bing Bai and Zhiqiong Guo. 2017. Dynamic complexity of mobile internet business ecosystem. In 4th International Conference on Systems and Informatics, ICSAI 2017, Hangzhou, China, November 11-13, 2017, 502–506. https://doi.org/10.1109/ICSAI.2017.8248344

[12]

Dingde Jiang, Liuwei Huo, and Houbing Song. 2020. Rethinking Behaviors and Activities of Base Stations in Mobile Cellular Networks Based on Big Data Analysis. IEEE Trans. Netw. Sci. Eng. 7, 1: 80–90. https://doi.org/10.1109/TNSE.2018.2861388

[13]

Dingde Jiang, Liuwei Huo, Zhihan Lv, Houbing Song, and Wenda Qin. 2018. A Joint Multi-Criteria Utility-Based Network Selection Approach for Vehicle-to-Infrastructure Networking. IEEE Trans. Intell. Transp. Syst. 19, 10: 3305–3319. https://doi.org/10.1109/TITS.2017.2778939

Digital Library

[14]

Dingde Jiang, Wenpan Li, and Haibin Lv. 2017. An energy-efficient cooperative multicast routing in multi-hop wire-less networks for smart medical applications. Neurocomputing 220: 160–169. https://doi.org/10.1016/j.neucom.2016.07.056

[15]

Dingde Jiang, Wenjuan Wang, Lei Shi, and Houbing Song. 2020. A Compressive Sensing-Based Approach to End-to-End Network Traffic Reconstruction. IEEE Trans. Netw. Sci. Eng. 7, 1: 507–519. https://doi.org/10.1109/TNSE.2018.2877597

[16]

Sheng Qi, Dingde Jiang, and Liuwei Huo. 2021. A Prediction Approach to End-to-End Traffic in Space Information Networks. Mob. Networks Appl. 26, 2: 726–735. https://doi.org/10.1007/s11036-019-01424-2

Digital Library

[17]

Prajapati, Arpita, Sakadasariya, Achyut and Patel, Jitisha. 2018. Software defined network: Future of networking}. 2018 2nd International Conference on Inventive Systems and Control (ICISC), 1351—1354.

[18]

Raychev, Jordan, Hristov, Georgi, Kinaneva, Diyana and Zahariev, Plamen. 2018. Modelling and Evaluation of Software Defined Network Architecture Based on Queueing Theory. In 2018 28th EAEEIE Annual Conference (EAEEIE).

[19]

Sandra Scott-Hayward, Sriram Natarajan, and Sakir Sezer. 2016. A Survey of Security in Software Defined Net-works. IEEE Commun. Surv. Tutorials 18, 1: 623–654. https://doi.org/10.1109/COMST.2015.2453114

Digital Library

[20]

Shalimov, Alexander, Zuikov, Dmitry, Zimarina, Daria, Pashkov, Vasily and Smeliansky, Ruslan. 2013. Advanced study of SDN/OpenFlow controllers. In Central & Eastern European Software Engineering Conference in Russia, 1–6.

[21]

Liuwei Huo, Dingde Jiang, Sheng Qi, Houbing Song, and Lei Miao. 2021. An AI-Based Adaptive Cognitive Modeling and Measurement Method of Network Traffic for EIS. Mob. Networks Appl. 26, 2: 575–585. https://doi.org/10.1007/s11036-019-01419-z

Digital Library

[22]

Paulo Fonseca, Ricardo Bennesby, Edjard de Souza Mota, and Alexandre Passito. 2012. A replication component for resilient OpenFlow-based networking. In 2012 IEEE Network Operations and Management Symposium, NOMS 2012, Maui, HI, USA, April 16-20, 2012, 933–939. https://doi.org/10.1109/NOMS.2012.6212011

[23]

Dingde Jiang, Liuwei Huo and Ya Li. 2018. Fine-granularity inference and estimations to network traffic for SDN. PLoS ONE 13, 5: e0194302.

[24]

Liuwei Huo, Dingde Jiang, Zhihan Lv, and Surjit Singh. 2020. An intelligent optimization-based traffic information acquirement approach to software-defined networking. Comput. Intell. 36, 1: 151–171. https://doi.org/10.1111/coin.12250

[25]

Feng Wang, Dingde Jiang and Sheng Qi. 2019. An adaptive routing algorithm for integrated information networks. China Commu-nications 16, 7: 195–206.

[26]

Chao Qi, Jiangxing Wu, Hongchao Hu, Guozhen Cheng, Wenyan Liu, Jianjian Ai, and Chao Yang. 2016. An inten-sive security architecture with multi-controller for SDN. In IEEE Conference on Computer Communications Work-shops, INFOCOM Workshops 2016, San Francisco, CA, USA, April 10-14, 2016, 401–402. https://doi.org/10.1109/INFCOMW.2016.7562109

[27]

Diego Kreutz, Fernando M v Ramos, and Paulo Verssimo. 2013. Towards secure and dependable software-defined networks. In Proceedings of the Second ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking, HotSDN 2013, The Chinese University of Hong Kong, Hong Kong, China, Friday, August 16, 2013, 55–60. https://doi.org/10.1145/2491185.2491199

Digital Library

[28]

Yuqing Wang, Dingde Jiang, Liuwei Huo, and Yong Zhao. 2021. A New Traffic Prediction Algorithm to Software Defined Networking. Mob. Networks Appl. 26, 2: 716–725. https://doi.org/10.1007/s11036-019-01423-3

Digital Library

[29]

Bolin Ma and Zheng Zhang. 2017. Security research of redundancy in mimic defense system. In 2017 3rd IEEE Internation-al Conference on Computer and Communications (ICCC).

[30]

Yuanyuan Chen, Wang Yao and Jianghua Luo. 2016. Research on the active defense security system based on cloud computing of wisdom campus network. In Control & Decision Conference.

[31]

Jing Xia, Zhiping Cai, Gang Hu and Ming Xu,. 2019. An Active Defense Solution for ARP Spoofing in OpenFlow Network. Chinese Journal of Electronics v.28, 01: 176–182.

[32]

Yoon, Geon, Lee, Soo-Gang, Kwon, Dae-Hyun, Kwon, Soon-Chang and Park, Yong-Oon. 2011. RAPIEnet based redundancy control system. IEEE, 140–145.

[33]

Dennis Tatang, Florian Quinkert, Joel Frank, Christian Röpke, and Thorsten Holz. 2017. SDN-Guard: Protecting SDN controllers against SDN rootkits. In 2017 IEEE Conference on Network Function Virtualization and Software De-fined Networks, NFV-SDN 2017, Berlin, Germany, November 6-8, 2017, 297–302. https://doi.org/10.1109/NFV-SDN.2017.8169856

[34]

Sarra Boukria, Mohamed Guerroumi, and Imed Romdhani. 2019. BCFR: Blockchain-based Controller Against False Flow Rule Injection in SDN. In 2019 IEEE Symposium on Computers and Communications, ISCC 2019, Barce-lona, Spain, June 29 - July 3, 2019, 1034–1039. https://doi.org/10.1109/ISCC47284.2019.8969780

[35]

Sadia Qureshi and Robin Braun. 2019. Mininet Topology: Mirror of the Optical Switch Fabric. In 29th International Telecommunication Networks and Applications Conference, ITNAC 2019, Auckland, New Zealand, November 27-29, 2019, 1–6. https://doi.org/10.1109/ITNAC46935.2019.9078014

[36]

Peter Peresni, Maciej Kuzniar, and Dejan Kostic. 2013. OpenFlow Needs You! A Call for a Discussion about a Cleaner OpenFlow API. In Second European Workshop on Software Defined Networks, EWSDN 2013, Berlin, Ger-many, October 10-11, 2013, 44–49. https://doi.org/10.1109/EWSDN.2013.14

Digital Library

[37]

Xu Zhang, Weigang Hou, Pengchao Han and Lei Guo. 2014. Design and Implementation of the Routing Function in the NOX Controller for Software-Defined Networks. Applied Mechanics & Materials 635–637: 1540–1543.

[38]

Tim Nelson, Andrew D Ferguson, Da Yu, Rodrigo Fonseca, and Shriram Krishnamurthi. 2015. Exodus: toward au-tomatic migration of enterprise network configurations to SDNs. In Proceedings of the 1st ACM SIGCOMM Sympo-sium on Software Defined Networking Research, SOSR ’15, Santa Clara, California, USA, June 17-18, 2015, 13:1–13:7. https://doi.org/10.1145/2774993.2774997

Digital Library

[39]

Yashar Ganjali and Amin Tootoonchian. 2010. HyperFlow: A Distributed Control Plane for OpenFlow. In 2010 In-ternet Network Management Workshop / Workshop on Research on Enterprise Networking, San Jose, CA, USA, April, 2010. Retrieved from https://www.usenix.org/conference/inmwren-10/hyperflow-distributed-control-plane-openflow

[40]

Liancheng Zhang, Yi Guo, Huiqiang Yuwen, and Yu Wang. 2016. A Port Hopping Based DoS Mitigation Scheme in SDN Network. In 12th International Conference on Computational Intelligence and Security, CIS 2016, Wuxi, China, December 16-19, 2016, 314–317. https://doi.org/10.1109/CIS.2016.0077

Cited By

Kondapalli PKrishna VPaul GVarghese M(2022)Energy Efficient Ad-hoc Network with Multicast Tree Topology for Wireless Sensor Applications2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC)10.1109/ICMNWC56175.2022.10032031(1-5)Online publication date: 2-Dec-2022
https://doi.org/10.1109/ICMNWC56175.2022.10032031

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ICCIR '22: Proceedings of the 2022 2nd International Conference on Control and Intelligent Robotics

June 2022

905 pages

ISBN:9781450397179

DOI:10.1145/3548608

Copyright © 2022 ACM.

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Published: 14 October 2022

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ICCIR 2022

ICCIR 2022: 2022 2nd International Conference on Control and Intelligent Robot

June 24 - 26, 2022

Nanjing, China

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Cited By

Kondapalli PKrishna VPaul GVarghese M(2022)Energy Efficient Ad-hoc Network with Multicast Tree Topology for Wireless Sensor Applications2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC)10.1109/ICMNWC56175.2022.10032031(1-5)Online publication date: 2-Dec-2022
https://doi.org/10.1109/ICMNWC56175.2022.10032031

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