Full Paper View Go Back

Unlocking Network Security and QoS: The Fusion of SDN, IoT, and Machine Learning: A Comprehensive Analysis

S. Aleem1 , S. Ahmed2

Section:Research Paper, Product Type: Journal
Vol.11 , Issue.6 , pp.15-22, Dec-2023

Online published on Dec 31, 2023


Copyright © S. Aleem, S. Ahmed . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library


XML View     PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: S. Aleem, S. Ahmed, “Unlocking Network Security and QoS: The Fusion of SDN, IoT, and Machine Learning: A Comprehensive Analysis,” International Journal of Scientific Research in Network Security and Communication, Vol.11, Issue.6, pp.15-22, 2023.

MLA Style Citation: S. Aleem, S. Ahmed "Unlocking Network Security and QoS: The Fusion of SDN, IoT, and Machine Learning: A Comprehensive Analysis." International Journal of Scientific Research in Network Security and Communication 11.6 (2023): 15-22.

APA Style Citation: S. Aleem, S. Ahmed, (2023). Unlocking Network Security and QoS: The Fusion of SDN, IoT, and Machine Learning: A Comprehensive Analysis. International Journal of Scientific Research in Network Security and Communication, 11(6), 15-22.

BibTex Style Citation:
@article{Aleem_2023,
author = {S. Aleem, S. Ahmed},
title = {Unlocking Network Security and QoS: The Fusion of SDN, IoT, and Machine Learning: A Comprehensive Analysis},
journal = {International Journal of Scientific Research in Network Security and Communication},
issue_date = {12 2023},
volume = {11},
Issue = {6},
month = {12},
year = {2023},
issn = {2347-2693},
pages = {15-22},
url = {https://www.isroset.org/journal/IJSRNSC/full_paper_view.php?paper_id=439},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRNSC/full_paper_view.php?paper_id=439
TI - Unlocking Network Security and QoS: The Fusion of SDN, IoT, and Machine Learning: A Comprehensive Analysis
T2 - International Journal of Scientific Research in Network Security and Communication
AU - S. Aleem, S. Ahmed
PY - 2023
DA - 2023/12/31
PB - IJCSE, Indore, INDIA
SP - 15-22
IS - 6
VL - 11
SN - 2347-2693
ER -

83 Views    117 Downloads    48 Downloads
  
  

Abstract :
The convergence of Software-Defined Networking (SDN) and the Internet of Things (IoT) has ushered in transformative changes, offering unparalleled levels of network flexibility, programmability, and connectivity. While this integration provides numerous benefits, it also introduces security challenges. Motivated by the imperative to fortify the security posture in this dynamically evolving landscape, this review paper explores the vulnerabilities, threats, and corresponding responses in the security landscape of SDN and IoT. Recognizing the critical need for proactive security measures, the paper underscores the potential of Quality of Service (QoS) empowered by Machine Learning (ML) as a solution. By harnessing ML, QoS emerges as a powerful means to proactively identify and mitigate potential attacks, offering an effective approach to enhance network security. The motivation behind integrating QoS with ML lies in its ability to ensure dependability, availability, and integrity, thereby instilling confidence in the reliability and resilience of the interconnected world. The paper goes through examination of challenges, delving into the proactive management of QoS within SDN, intricacies of IoT network architectures, and the unique features and limitations of IoT systems. Furthermore, it comprehensively addresses potential countermeasures for various security threats, such as Denial of Service (DOS), Man-in-the-Middle (MITM) attacks, and Ransomware attacks, particularly on devices with limited resources. This abstract provides a concise yet comprehensive overview of the paper`s motivations, emphasizing the urgency and significance of the proposed solutions for securing modern network environments.

Key-Words / Index Term :
SDN, IoT, QoS, ML, DOS, MITM, WSN, M2M.

References :
[1] Restuccia, F., D’Oro, S., Melodia, T. "Securing the Internet of Things in the Age of Machine Learning and Software-Defined Networking," IEEE Internet Things J, vol. 5, no. 6, pp. 4829–4842, Dec. 2018, doi: 10.1109/JIOT.2018.2846040.
[2] Nauman, A., Qadri, Y. A., Amjad, M., bin Zikria, Y., Afzal, M. K., Kim, S. W. "Special Section On Mobile Multimedia: Methodology And Application Multimedia Internet Of Things: A Comprehensive Survey," pp. 1-54, doi: 10.1109/ACCESS.2020.2964280.
[3] Miorandi, D., Sicari, S., de Pellegrini, F., Chlamtac, I. "Internet of things: Vision, applications and research challenges," Ad Hoc Networks, vol. 10, no. 7, Elsevier B.V., pp. 1497–1516, 2012, doi: 10.1016/j.adhoc.2012.02.016.
[4] Sarker, I. H., Hoque, M. M., Uddin, M. K., Alsanoosy, T. "Mobile Data Science and Intelligent Apps: Concepts, AI-Based Modeling and Research Directions," Mobile Networks and Applications, vol. 26, no. 1, 2021, doi: pp 285–303 , 10.1007/s11036-020-01650-z.
[5] Cui, L., Yang, S., Chen, F., Ming, Z., Lu, N., Qin, J. "A survey on the application of machine learning for the Internet of Things," International Journal of Machine Learning and Cybernetics, vol. 9, no. 8, 2018, pp 1399-1417, doi: 10.1007/s13042-018-0834-5.
[6] Hammad, K., Moubayed, A., Primak, S. L., Shami, A. "QoS-Aware Energy and Jitter-Efficient Downlink Predictive Scheduler for Heterogeneous Traffic LTE Networks," IEEE Trans Mob Comput, vol. 17, no. 6, 2018, pp 1468 - 1483 doi: 10.1109/TMC.2017.2771353.
[7] Bhat, O., Gokhale, P., Bhat, S. "Introduction to IOT," International Advanced Research Journal in Science, Engineering and Technology ISO, vol. 3297, no. 1, 2007, pp 41-44 , doi: 10.17148/IARJSET.2018.517.
[8] Mudgal, S., Pranjale, S., Mahajan, V. "Impact of Cyber-Attacks on Economy of Smart Grid and their Prevention," U.Porto Journal of Engineering (2022), pp. 51 – 64, DOI: 10.24840/2183-6493_008.002_0005.
[9] Qin, Q., Poularakis, K., Tassiulas, L. "Bringing Intelligence at the Network Data Plane for Internet of Things Security," "IoT for Defense and National Security," 2022, Publisher Willey , pp- ch 14 doi: 10.1002/9781119892199.
[10] Nguyen, K. T., Laurent, M., Oualha, N. "Survey on secure communication protocols for the Internet of Things," Ad Hoc Networks, vol. 32, pp. 17–31, Sep. 2015, doi: 10.1016/j.adhoc.2015.01.006.
[11] Airehrour, D., Gutierrez, J., & Ray, S. K. (2016). "Secure routing for Internet of Things: A survey." Journal of Network and Computer Applications, pp 198-213 doi: 10.1016/j.jnca.2016.03.006.
[12] Vasilomanolakis, E., Daubert, J., Luthra, M., Gazis, V., Wiesmaier, A., & Kikiras, P. (2016). "On the Security and Privacy of Internet of Things Architectures and Systems." In Proceedings - 2015 International Workshop on Secure Internet of Things, SIoT 2015, pp. 49–57. doi: 10.1109/SIOT.2015.9.
[13] Zhang, C., & Green, R. (2015). "Communication security in Internet of Things: Preventive measure and avoid DDoS attack over IoT network." Simulation Series, 47(3), pp 8–15.
[14] Lygerou, I., Srinivasa, S., Vasilomanolakis, E., Stergiopoulos, G., & Gritzalis, D. (2023). "Correction to: A decentralized honeypot for IoT Protocols based on Android devices." International Journal of Information Security, 21(6), pp 1211-1222. doi: 10.1007/s10207-022-00605-7.
[15] Krishnan, P., & Achuthan, K. (2019). "Managing network functions in stateful application aware SDN." Communications in Computer and Information Science. Pp 88-103, doi: 10.1007/978-981-13-5826-5_7.
[16] Hossen, M. A., & Sang, J. Y. (2019). "Q-Learning Based Multi-Objective Clustering Algorithm for Cognitive Radio Ad Hoc Networks." IEEE Access., pp 181959 - 181971 doi: 10.1109/ACCESS.2019.2959313.
[17] Schaller, S., & Hood, D. (2017). "Software-defined networking architecture standardization." Computers Standards & Interfaces, 54, pp 197–202. doi: 10.1016/j.csi.2017.01.005.
[18] Lara, A., Kolasani, A., & Ramamurthy, B. (2014). "Network innovation using OpenFlow: a survey." IEEE Communications Surveys and Tutorials, 16(1),pp 493–512. doi: 10.1109/SURV.2013.081313.00105.
[19] Huang, X., et al. (2015). "Cost-effective authentic and anonymous data sharing with forward security." IEEE Transactions on Computers, 64(4), pp 971–983. doi: 10.1109/TC.2014.2315619.
[20] Al-Garadi, M. A., Mohamed, A., Al-Ali, A. K., Du, X., Ali, I., & Guizani, M. (2020). "A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security." IEEE Communications Surveys and Tutorials, 22(3), pp 1646–1685. doi: 10.1109/COMST.2020.2988293.
[21] F Restuccia, S D`Oro, & T Melodia,” Securing the Internet of Things in the Age of Machine Learning and Software-Defined Networking” IEEE Internet of Things Journal, 5(6), PP 4829-4842. doi: 10.1109/JIOT.2018.2831526.
[22] G. Kim, S. Lee, and S. Kim, "A novel hybrid intrusion detection method integrating anomaly detection with misuse detection," Expert Syst Appl, vol. 41, no. 4 PART 2, pp. 1690–1700, 2014, doi: 10.1016/j.eswa.2013.08.066.
[23] D Rahmati; S A Hamid, "Classified Round Robin: A Simple Prioritized Arbitration to Equip Best Effort NoCs With Effective Hard QoS," IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 37, issue 1, pp. 257 - 269, January 2018. DOI: 10.1109/TCAD.2017.2693263.
[24] S. Sicari, A. Rizzardi, L. A. Grieco, and A. Coen-Porisini, "Security, privacy and trust in Internet of things: The road ahead," Computer Networks, vol. 76, pp. 146–164, Jan. 15, 2015. doi: 10.1016/j.comnet.2014.11.008.
[25] N. McLaughlin et al., "Deep android malware detection," in CODASPY 2017 - Proceedings of the 7th ACM Conference on Data and Application Security and Privacy, Mar. 2017, pp. 301–308. doi: 10.1145/3029806.3029823.
[26] S. Skorobogatov, "Compromising device security via NVM controller vulnerability," 2020 IEEE Physical Assurance and Inspection of Electronics (PAINE), Washington, DC, USA, 2020, pp. 1-6, doi: 10.1109/PAINE49178.2020.933
[27] S. Babar, A. Stango, N. Prasad, J. Sen, and R. Prasad, "Proposed embedded security framework for Internet of Things (IoT)," in 2011 2nd International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace and Electronic Systems Technology, Wireless VITAE 2011, 2011. Pp art. no. 5940923 doi: 10.1109/WIRELESSVITAE.2011.5940923.
[28] K. Petersen, R. Feldt, S. Mujtaba, and M. Mattsson, "Systematic Mapping Studies in Software Engineering." Pp 1-10.
[29] Renya Nath N, Hiran V Nath. "Critical analysis of the layered and systematic approaches for understanding IoT security threats and challenges," IEEE Computers and Electrical Engineering, Volume 100, pp 2-17, May 2022.
[30] I. Ahammad, M. A. Rahman Khan, Z. U. Salehin, M. Uddin, and S. J. Soheli, "Improvement of QoS in an IoT ecosystem by integrating fog computing and SDN," International Journal of Cloud Applications and Computing, vol. 11, no. 2, pp. 48–66, Apr. 2021, doi: 10.4018/IJCAC.2021040104.
[31] G. Kurt et al., “A Vision and Framework for the High-Altitude Platform Station (HAPS) Networks of the Future,” Jul. 2020, pp 729-799.
[32] A. Roy, T. Acharya, and S. DasBit, “Quality of service in delay tolerant networks: A survey,” Computer Networks, vol. 130. Elsevier B.V., pp. 121–133, Jan. 15, 2018. doi: 10.1016/j.comnet.2017.11.010.
[33] F. S Biswas, “QOS-AWARE SCHEDULING,” United State Patent, Patent no. US 9,135,072 B2, Sep. 2015, Corpus ID: 44736585, pp 1-10 .
[34] J. A. C. Gary G. Warden, “Systems and methods for providing quality of service (QoS) in an environment that does not normally support QoS features,” Jun. 2008. Pp 1-12.
[35] S. Kalyani, “Measurement and Analysis of QoS Parameters in RPL Network,” 2018, pp. 307-312.
[36] M. Sedrati, “Evaluation of QoS parameters with RPL protocol in the internet of things,” in ACM International Conference Proceeding Series, Jul. 2017, vol. Part F130657, pp. 86–91. doi: 10.1145/3129186.3129204.
[37] M. R. Parsaei, M. J. Sobouti, S. Raouf, and R. Javidan, “Network Traffic Classification using Machine Learning Techniques over Software Defined Networks,” 2017. Pp 219-225.
[38] A. ?olakovi? and M. Hadžiali?, “Internet of Things (IoT): A review of enabling technologies, challenges, and open research issues,” Computer Networks, vol. 144. Elsevier B.V., pp. 17–39, Oct. 24, 2018. doi: 10.1016/j.comnet.2018.07.017.
[39] Y. Yamsanwar and S. Sutar, “Performance analysis of wireless sensor networks for QoS,” in 2017 International Conference on Big Data, IoT and Data Science, BID 2017, 2018, vol. 2018-January, pp 120-123, doi: 10.1109/BID.2017.8336584.
[40] Vivek S., “Performance analysis of FMAC protocol for reporting rate in wireless sensor networks,” 2016, pp1-5 .
[41] J. Granjal, E. Monteiro, and J. Sa Silva, “Security for the internet of things: A survey of existing protocols and open research issues,” IEEE Communications Surveys and Tutorials, vol. 17, no. 3, pp. 1294–1312, Jul. 2015, doi: 10.1109/COMST.2015.2388550.
[42] M Díaz, C Martín, & B Rubio” State-of-the-art, challenges, and open issues in the integration of Internet of Things and cloud computing.” Journal of Network and Computer Applications, vol. 67, pp 99-117.
[43] D. Gil, A. Ferrández, H. Mora-Mora, and J. Peral, “Internet of things: A review of surveys based on context aware intelligent services,” Sensors (Switzerland), vol. 16, no. 7. MDPI AG, Jul. 11, 2016.pp 1-23, doi: 10.3390/s16071069.
[44] G. White, V. Nallur, and S. Clarke, “Quality of service approaches in IoT: A systematic mapping,” Journal of Systems and Software, vol. 132, pp. 186–203, Oct. 2017, doi: 10.1016/j.jss.2017.05.125.
[45] A. Riahi Sfar, E. Natalizio, Y. Challal, and Z. Chtourou, “A roadmap for security challenges in the Internet of Things,” Digital Communications and Networks, vol. 4, no. 2, pp. 118–137, Apr. 2018, doi: 10.1016/j.dcan.2017.04.003.
[46] M. binti Mohamad Noor and W. H. Hassan, “Current research on Internet of Things (IoT) security: A survey,” Computer Networks, vol. 148, 2019, pp 283- 294 doi: 10.1016/j.comnet.2018.11.025.
[47] T. T. T. Nguyen and G. Armitage, “A survey of techniques for internet traffic classification using machine learning,” IEEE Communications Surveys and Tutorials, vol. 10, no. 4. 2008, pp 56-76, doi: 10.1109/SURV.2008.080406.
[48] S A Fadhil,”. Internet of Things security threats and key technologies. Journal of Discrete Mathematical Sciences and Cryptography, Pages 1951-1957, 25 Oct 2021.
[49] Sahraoui, S., & Bilami, A. (2015). Efficient HIP-based approach to ensure lightweight end-to-end security in the internet of things. Computer Networks, Volume 19 14 November 2015, PP 26-45.
[50] S. Chen and K. Nahrstedt, “An Overview of Quality-of-Service Routing for Next-Generation High-speed Networks: Problems and Solutions.” Pp 64-79.
[51] M. U. Akram, M. Rizwan Asghar, M. A. Naeem, H. A. Khan, and H. Farooq, "Secure QoS Provisioning for SDN-based IoT Networks using Machine Learning," IEEE Access, vol. 9, pp. 11120-11136, 2021. DOI: 10.1109/ACCESS.2021.305113.
[52] K. K. Patel, & S. M Patel,” Internet of Things (IoT): Definition, Characteristics, Architecture, Enabling Technologies, Application & Future Challenges” International Journal of Engineering Science and Computing, May 2016, PP- 6122-6131.
[53] P Sethi, S R Sarangi, “ Internet of Things: Architectures, Protocols, and Applications. Journal of Electrical and Computer Engineering” Volume 2017, Article ID 9324035. Pp 1-25, doi:10.1155/2017/9324035.

Authorization Required

 

You do not have rights to view the full text article.
Please contact administration for subscription to Journal or individual article.
Mail us at ijsrnsc@gmail.com or view contact page for more details.

Impact Factor

Journals Contents

Information

Downloads

Digital Certificate

Go to Navigation