A Reliable System To Detect Security Attacks In A Scalable SDN Architecture.

Ovi, Md. Sultanul Islam; Mahmud, Nafil; Oishee, Abida Taskin

dc.contributor.author	Ovi, Md. Sultanul Islam
dc.contributor.author	Mahmud, Nafil
dc.contributor.author	Oishee, Abida Taskin
dc.date.accessioned	2022-04-07T05:00:59Z
dc.date.available	2022-04-07T05:00:59Z
dc.date.issued	2021-03-30
dc.identifier.citation	[1] R. Kl¨oti, V. Kotronis, and P. Smith, “Openflow: A security analysis,” in 2013 21st IEEE International Conference on Network Protocols (ICNP), pp. 1–6, IEEE, 2013. [2] S. Knight, H. X. Nguyen, N. Falkner, R. Bowden, and M. Roughan, “The internet topology zoo,” IEEE Journal on Selected Areas in Communications, vol. 29, no. 9, pp. 1765–1775, 2011. [3] D. Kreutz, F. M. Ramos, P. E. Verissimo, C. E. Rothenberg, S. Azodolmolky, and S. Uhlig, “Software-defined networking: A comprehensive survey,” Proceedings of the IEEE, vol. 103, no. 1, pp. 14–76, 2014. [4] S. Scott-Hayward, S. Natarajan, and S. Sezer, “A survey of security in software defined networks,” IEEE Communications Surveys & Tutorials, vol. 18, no. 1, pp. 623–654, 2015. [5] S. T. Ali, V. Sivaraman, A. Radford, and S. Jha, “A survey of securing networks using software defined networking,” IEEE transactions on reliability, vol. 64, no. 3, pp. 1086– 1097, 2015. [6] D. Kreutz, F. M. Ramos, and P. Verissimo, “Towards secure and dependable softwaredefined networks,” in Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking, pp. 55–60, 2013. [7] A. Feldmann, P. Heyder, M. Kreutzer, S. Schmid, J.-P. Seifert, H. Shulman, K. Thimmaraju, M. Waidner, and J. Sieberg, “Netco: Reliable routing with unreliable routers,” in 2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshop (DSN-W), pp. 128–135, IEEE, 2016. [8] A. Shaghaghi, M. A. Kaafar, and S. Jha, “Wedgetail: An intrusion prevention system for the data plane of software defined networks,” in Proceedings of the 2017 ACM on Asia Conference on Computer and Communications Security, pp. 849–861, 2017. [9] A. T. Mizrak, Y.-C. Cheng, K. Marzullo, and S. Savage, “Detecting and isolating malicious routers,” IEEE Transactions on Dependable and Secure Computing, vol. 3, no. 3, pp. 230– 244, 2006. 35 REFERENCES 36 [10] A. T. Mzrak, S. Savage, and K. Marzullo, “Detecting malicious packet losses,” IEEE Transactions on Parallel and distributed systems, vol. 20, no. 2, pp. 191–206, 2008. [11] T. H.-J. Kim, C. Basescu, L. Jia, S. B. Lee, Y.-C. Hu, and A. Perrig, “Lightweight source authentication and path validation,” in Proceedings of the 2014 ACM Conference on SIGCOMM, pp. 271–282, 2014. [12] S. Lee, T. Wong, and H. S. Kim, “Secure split assignment trajectory sampling: A malicious router detection system,” in International Conference on Dependable Systems and Networks (DSN’06), pp. 333–342, IEEE, 2006. [13] P.-W. Chi, C.-T. Kuo, J.-W. Guo, and C.-L. Lei, “How to detect a compromised sdn switch,” in Proceedings of the 2015 1st IEEE Conference on Network Softwarization (Net- Soft), pp. 1–6, IEEE, 2015. [14] R. Ghannam and A. Chung, “Handling malicious switches in software defined networks,” in NOMS 2016-2016 IEEE/IFIP Network Operations and Management Symposium, pp. 1245–1248, IEEE, 2016. [15] Y. J. Zhu and L. Jacob, “On making tcp robust against spurious retransmissions,” Computer communications, vol. 28, no. 1, pp. 25–36, 2005. [16] M. Dhawan, R. Poddar, K. Mahajan, and V. Mann, “Sphinx: detecting security attacks in software-defined networks.,” in Ndss, vol. 15, pp. 8–11, 2015. [17] N. Handigol, B. Heller, V. Jeyakumar, D. Mazi`eres, and N. McKeown, “I know what your packet did last hop: Using packet histories to troubleshoot networks,” in 11th fUSENIXg Symposium on Networked Systems Design and Implementation (fNSDIg 14), pp. 71–85, 2014. [18] P. Kazemian, G. Varghese, and N. McKeown, “Header space analysis: Static checking for networks,” in Presented as part of the 9th fUSENIXg Symposium on Networked Systems Design and Implementation (fNSDIg 12), pp. 113–126, 2012. [19] H. Zhou, C.Wu, C. Yang, P.Wang, Q. Yang, Z. Lu, and Q. Cheng, “Sdn-rdcd: A real-time and reliable method for detecting compromised sdn devices,” IEEE/ACM Transactions on Networking, vol. 26, no. 5, pp. 2048–2061, 2018. [20] P. Zhang, S. Xu, Z. Yang, H. Li, Q. Li, H.Wang, and C. Hu, “Foces: Detecting forwarding anomalies in software defined networks,” in 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), pp. 830–840, IEEE, 2018. [21] T. Shimizu, N. Kitagawa, K. Ohshima, and N. Yamai, “Whiterabbit: Scalable softwaredefined network data-plane verification method through time scheduling,” IEEE Access, vol. 7, pp. 97296–97306, 2019. REFERENCES 37 [22] K.-F. Lee, H.-W. Hon, and R. Reddy, “An overview of the sphinx speech recognition system,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 38, no. 1, pp. 35–45, 1990. [23] N. Pelekis, I. Kopanakis, C. Panagiotakis, and Y. Theodoridis, “Unsupervised trajectory sampling,” in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 17–33, Springer, 2010. [24] S. Vassilvitskii and D. Arthur, “k-means++: The advantages of careful seeding,” in Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, pp. 1027–1035, 2006. [25] M. K. Pakhira, “A linear time-complexity k-means algorithm using cluster shifting,” in 2014 International Conference on Computational Intelligence and Communication Networks, pp. 1047–1051, IEEE, 2014. [26] A. Grønlund, K. G. Larsen, A. Mathiasen, J. S. Nielsen, S. Schneider, and M. Song, “Fast exact k-means, k-medians and bregman divergence clustering in 1d,” arXiv preprint arXiv:1701.07204, 2017. [27] X. Wu, “Optimal quantization by matrix searching,” Journal of algorithms, vol. 12, no. 4, pp. 663–673, 1991. [28] T. Mizrahi and Y. Moses, “Time4: Time for sdn,” IEEE Transactions on Network and Service Management, vol. 13, no. 3, pp. 433–446, 2016. [29] S. Badotra and J. Singh, “Open daylight as a controller for software defined networking.,” International Journal of Advanced Research in Computer Science, vol. 8, no. 5, 2017. [30] P. Berde, M. Gerola, J. Hart, Y. Higuchi, M. Kobayashi, T. Koide, B. Lantz, B. O’Connor, P. Radoslavov, W. Snow, et al., “Onos: towards an open, distributed sdn os,” in Proceedings of the third workshop on Hot topics in software defined networking, pp. 1–6, 2014. [31] N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, S. Shenker, and J. Turner, “Openflow: enabling innovation in campus networks,” ACM SIGCOMM computer communication review, vol. 38, no. 2, pp. 69–74, 2008. [32] B. Pfaff, J. Pettit, T. Koponen, E. Jackson, A. Zhou, J. Rajahalme, J. Gross, A. Wang, J. Stringer, P. Shelar, et al., “The design and implementation of open vswitch,” in 12th fUSENIXg Symposium on Networked Systems Design and Implementation (fNSDIg 15), pp. 117–130, 2015. [33] U. Lamping and E.Warnicke, “Wireshark user’s guide,” Interface, vol. 4, no. 6, p. 1, 2004. REFERENCES 38 [34] D. Mills, RFC1305: Network Time Protocol (Version 3) Specification, Implementation. RFC Editor, 1992. [35] K. Correll, N. Barendt, and M. Branicky, “Design considerations for software only implementations of the ieee 1588 precision time protocol,” in Conference on IEEE, vol. 1588, pp. 11–15, Citeseer, 2005. [36] T. Mizrahi and Y. Moses, “Reverseptp: A software defined networking approach to clock synchronization,” in Proceedings of the third workshop on Hot topics in software defined networking, pp. 203–204, 2014.	en_US
dc.identifier.uri	http://hdl.handle.net/123456789/1307
dc.description	Supervised by Dr. Muhammad Mahbub Alam Professor Department of Computer Science and Engineering(CSE) Islamic University of Technology(IUT)	en_US
dc.description.abstract	Software-Defined Network (SDN) is a promising solution of network virtualization. But it is vulnerable to attacks by corrupted switches as existing detection mechanisms do not work in this environment. A corrupted switch can also compromise the SDN controller. In this paper, we propose a detection mechanism that can detect both compromised SDN switches and controllers. Our main idea is to cluster to the frequently used devices and then collect statistics of those switches to create the expected and actual path for a packet. Thus, we can identify specific compromised switches and also specify the attacks. The detection mechanism is not dependent on the controller performance as we collect statistics of the switches in real-time and in a periodic manner.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering (CSE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.title	A Reliable System To Detect Security Attacks In A Scalable SDN Architecture.	en_US
dc.type	Thesis	en_US