A Reliable and Secure Inter-And Intra-State Routing Protocol for VoIP communication

A Reliable and Secure Inter-And Intra-State Routing Protocol for VoIP communication

  IJETT-book-cover           
  
© 2022 by IJETT Journal
Volume-70 Issue-7
Year of Publication : 2022
Authors : Vinod Kumar, Om Prakash Roy
DOI : 10.14445/22315381/IJETT-V70I7P250

How to Cite?

Vinod Kumar, Om Prakash Roy, "A Reliable and Secure Inter-And Intra-State Routing Protocol for VoIP communication" International Journal of Engineering Trends and Technology, vol. 70, no. 7, pp. 479-490, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I7P250

Abstract
Technological advancements increase the demand for communication over a reliable Voice over Internet Protocol (VoIP) network. The data communication in such a network is often attacked by intruders, which requires the implementation of a secure system for transmission. This paper presents a robust data communication network in which the proposed structure consists of two block architectures: Inter-State Routing (INTER-SR) and Intra State Routing (INTRA-SR). This architecture handles the data communication for the intra-structure route, and the INTRA-SR block handles inter structure route and data communication over a network. The proposed work focuses on constructing the deployment model using the distance formula to attain appropriate route discovery by considering 60 nodes. The inter-state architecture is developed using the interpolation structure and Neural Network to classify the nodes. Further comparison is performed with the approach such as a support vector machine (SVM). The outcome is simulated, considering the classification accuracy, throughput, and packet delivery ratio (PDR) rate to determine its robustness. The network's reliability is tested by improvement in the throughput and the PDR, taking a ratio of how many nodes are accepted to be in the network. It is observed that the throughput increases significantly when there is an increase in the reliable nodes, whereas the PDR is radical. The results show that the PDR rate improved by 15% and the throughput rate revamped by 21% compared to other classification approaches.

Keywords
Neural Network, Reliability, Security, Support Vector Machine, VoIP.

Reference
[1] Goode, B, “Voice over internet protocol (VoIP),” Proceedings of the IEEE, vol.90, no.9, pp.1495-1517, 2002.
[2] Chakraborty T., Misra I.S., Prasad R., “Technique for Improving VoIP Performance over Wireless LANs”, In: VoIP Technology: Applications and Challenges,” Springer Series in Wireless Technology. Springer, Cham, 2019.
[3] Vennila, G., Manikandan, M. S. K., and Suresh, M. N, “Dynamic voice spammers detection using Hidden Markov Model for Voice over Internet Protocol network,” Computers & Security, vol.73, pp.1-16, 2018.
[4] Akbar, M. A., and Farooq, M., “Securing SIP-based VoIP infrastructure against flooding attacks and Spam over IP Telephony,” Knowledge and information systems, vol.38, no.2, pp.491-510, 2014.
[5] Kaur, T., & Kumar, D, “A survey on QoS mechanisms in WSN for computational intelligence based routing protocols,” Wireless Networks, 26(4) 2465-2486.
[6] Gandhi, U. D., Kumar, P. M., Varatharajan, R., Manogaran, G., Sundarasekar, R., & Kadu, S, “ HIoTPOT: surveillance on IoT devices against recent threats,” Wireless personal communications, vol.103, no.2 , pp.1179-1194, 2013.
[7] Anbar, M., Abdullah, R., Al-Tamimi, B. N., & Hussain, A, “A machine learning approach to detect router advertisement flooding attacks in next-generation IPv6 networks,” Cognitive Computation, vol.10, no.2, pp.201-214, 2018.
[8] Vinnarasi, F. S. F., & Chandrasekar, A, “VANET routing protocol with traffic aware approach,” International Journal of Advanced Intelligence Paradigms, vol.12, no. (1-2) , pp.3-13, 2019.
[9] Thomas Porter, C. I. S. S. P., & CCNP, C, “Practical VoIP Security,” Elsevier, 2006.
[10] Paul, S., & Pandit, M. K, “A QoS-Enhanced Smart Packet Scheduler for Multi-core Processors in Intelligent Routers Using Machine Learning,” In Smart Intelligent Computing and Applications, Springer, Singapore, pp. 713-720, 2019.
[11] Troia, S., Rodriguez, A., Martín, I., Hernández, J. A., De Dios, O. G., Alvizu, R., ... & Maier, G, “Machine-learning-assisted routing in SDN-based optical networks”, In 2018 European Conference on Optical Communication (ECOC), IEEE, pp.1-3, 2018.
[12] Oo, T. T., & Don, A. A, “Design and Implementation of Data and Voice Redundancy and Line Aggregation for VoIP with multiple links,” International Journal of Engineering & Technology, vol.8, no.1.6, pp. 23-29, 2019.
[13] Xu, J., Wang, J., Qi, Q., Sun, H., & He, B, “Deep neural networks for application awareness in SDN-based network,” In 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), IEEE, pp. 1-6, 2018.
[14] Sun, L., and Ifeachor, E. C, “Voice quality prediction models and their application in VoIP networks,” IEEE transactions on multimedia, Digital Object Identifier, vol.8, no.4, pp. 809-820, 2006.
[15] Khatouni, A. S., Seddigh, N., Nandy, B., & Zincir-Heywood, N, “Machine Learning Based Classification Accuracy of Encrypted Service Channels: Analysis of Various Factors,” Journal of Network and Systems Management, vol.29, no.1, pp.1-27, 2021.
[16] Moller, D. P, “Cybersecurity in Digital Transformation: Scope and Applications,” Springer Nature, 2020.
[17] Elmi, A. H., Ibrahim, S., & Sallehuddin, R., “Detecting sim box fraud using neural network,” In IT Convergence and Security 2012, Springer, Dordrecht, pp.575-582, 2013.
[18] Xiao, X., Wang, Z., Li, Q., Xia, S., & Jiang, Y, “Back‐propagation neural network on Markov chains from system call sequences: a new approach for detecting Android malware with system call sequences,” IET Information Security, vol.11, no.1, pp.8-15, 2017.
[19] Al-Akhras, M., Zedan, H., John, R., & Almomani, I, “Non-intrusive speech quality prediction in VoIP networks using a neural network approach,” Neurocomputing, vol.72, no.(10-12), pp.2595-2608, 2009.
[20] Maheshwari, S., Mahapatra, S., Kumar, C. S., & Vasu, K, “A joint parametric prediction model for wireless internet traffic using Hidden Markov Model,” Wireless networks, vol.19, no.6, pp.1171-1185, 2013.
[21] Jaiswal, R., & Hines, A, “Towards a Non-Intrusive Context-Aware Speech Quality Model,” In 2020 31st Irish Signals and Systems Conference (ISSC), IEEE, pp.1-5, 2020.
[22] Rebahi, Y., Nassar, M., Magedanz, T., & Festor, O, “A survey on fraud and service misuse in voice over IP (VoIP) networks,” Information Security Technical Report, vol.16, no.1, pp. 12-19, 2011.
[23] Kumar, N., & Kumar, D, “An Improved Grey Wolf Optimization-based Learning of Artificial Neural Network for Medical Data Classification,” Journal of Information and Communication Technology, vol.20, no.2, pp. 213-248, 2021.
[24] Xu, L., Zhou, X., Lin, X., Ren, Y., Qin, Y., & Liu, J., “A New Loss Function for Traffic Classification Task on Dramatic Imbalanced Datasets,” In ICC 2020-2020 IEEE International Conference on Communications (ICC), IEEE, pp. 1-7, 2020.
[25] Gupta, S. K., Kumar, S., Tyagi, S., & Tanwar, S, “Energy efficient routing protocols for wireless sensor network,” In Handbook of Wireless Sensor Networks: Issues and Challenges in Current Scenario's Springer, Cham, pp. 275-298, 2020.
[26] Wang, L., Lehman, V., Hoque, A. M., Zhang, B., Yu, Y., & Zhang, L, “A secure link state routing protocol for NDN,” IEEE Access, vol.6 , pp.10470-10482, 2018.
[27] Ramalho, M, “Intra-and Inter-domain multicast routing protocols: A survey and taxonomy,” IEEE Communications Surveys & Tutorials, vol.3, no.1, pp. 2-25, 2000.
[28] Chennikara-Varghese, J., Chen, W., Altintas, O., & Cai, S, “Survey of routing protocols for inter-vehicle communications,” In 2006 Third Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services, IEEE, pp.1-5, 2006.
[29] Altın, A., Fortz, B., Thorup, M., & Ümit, H, “Intra-domain traffic engineering with shortest path routing protocols,” Annals of Operations Research, vol.204, no.1, pp.65-95, 2013.
[30] Qu, D., Vetter, B. M., Wang, F., Narayan, R., Wu, S. F., Hou, Y. F. ... & Sargor, C, “Statistical anomaly detection for link-state routing protocols,” In Proceedings Sixth International Conference on Network Protocols (Cat. No. 98TB100256), IEEE, pp. 62-70, 1998.
[31] Singh, A. V., Juyal, V., & Saggar, R., “Trust based intelligent routing algorithm for delay tolerant network using artificial neural network,” Wireless Networks, vol.23, no.3, pp. 693-702.
[32] Rianto Nugroho, Fuad Djauhari, Galih Damas Priambodo, Novi Azman, “ATM VSAT Switchover Planning Telkom-1 Satellite Case Study to BRIsat Satellite,” International Journal of Engineering Trends and Technology(IJETT), vol. 69, no.11, pp.128-133, 2021.
[33] Vennila, G., Manikandan, M. S. K., & Suresh, M. N, “Detection and prevention of spam over Internet telephony in Voice over Internet Protocol networks using Markov chain with incremental SVM,” International Journal of Communication Systems, vol.30, no.11, pp.3255,
[34] Vijayakumar, M., & Karthikeyani, V, “A Novel Approach of DBPQ with RSSI Queuing Technique for VoIP QoS over MANET,” Indian Journal of Science and Technology, vol.9, vol.30, pp.1-8, 2016.
[35] Militani, D. R., de Moraes, H. P., Rosa, R. L., Wuttisittikulkij, L., Ramírez, M. A., & Rodríguez, D. Z., “Enhanced Routing Algorithm Based on Reinforcement Machine Learning,” A Case of VoIP Service, 2021.
[36] Rattal, S., Badri, A., & Moughit, M., “A new wireless VoIP signaling device supporting SIP and H. 323 protocols,” Journal of Computer Networks and Communications, vol.2014, 2014.
[37] Sathu, H., and Shah, M. A., “Performance comparison of VoIP codecs on multiple operating systems using IPv4 and IPv6,” International Journal of e-Education, e-Business, e-Management and e-Learning, vol.2l, no.2 , pp.122, 2012.
[38] R. Surendiran, K. Alagarsamy, "Privacy Conserved Access Control Enforcement in MCC Network with Multilayer Encryption," International Journal of Engineering Trends and Technology, vol. 4, no. 5, pp.2217-2224, 2013. https://doi.org/10.14445/22315381/IJETT-V4I5P174
[39] Sielay Gebru, Prachi Kadam, “Simulation Based performance evaluation and comparison of wired VoIP services over UDP and SCTP protocol,” International Journal of Engineering Trends and Technology (IJETT), vol.33, no.9, pp.462-467, 2016.
[40] Kumar, V. & Roy, O. P, “QoS-Based Machine Learning Approach for Security of VoIP Services,” International Journal of Engineering Trends and Technology (IJETT), vol.70, no.2, pp.214-220, 2022.
[41] Newton, P. C., & Ramkumar, K., “TACA: Throughput Aware Call Admission Control Algorithm for VoIP Users in Mobile Networks,” In Advances in Computer and Computational Sciences, Springer, Singapore, pp.259-270, 2017.
[42] A. Srikrishnan, Dr. Arun Raaza & Dr. B. Ebenezer Abishek, “Internet of Things (Iot) Network Security using Quantum Key Distribution Algorithm,” International Journal of Engineering Trends and Technology(IJETT), vol.70, no.2 , pp.19-23, 2022.
[43] Chen, D. R., Chen, L. C., Chen, M. Y., and Hsu, M. Y, “A coverage-aware and energy-efficient protocol for the distributed wireless sensor networks,” Computer Communications, vol.137, pp. 15-31, 2019.
[44] Schmidt, S., Mazurczyk, W., Kulesza, R., Keller, J., & Caviglione, L., “Exploiting IP telephony with silence suppression for hidden data transfers,” Computers & Security, vol.79, pp.17-32, 2018.
[45] Nassar, M., & Festor, O., “Monitoring SIP traffic using support vector machines, In International Workshop on Recent Advances in Intrusion Detection,” Springer, Berlin, Heidelberg, pp. 311-330, 2008.
[46] Rath, M., Rout, U. P., Pujari, N., Nanda, S. K., & Panda, S. P., “Congestion control mechanism for real time traffic in mobile adhoc networks,” In Computer communication, networking and internet security, Springer, Singapore, pp. 149-156, 2017.
[47] Ahson, S. A., and Ilyas, M. (Eds.), “VoIP Handbook: Applications, technologies, reliability, and security,” CRC Press, 2008.