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EESSMT: An Energy Efficient Hybrid Scheme for Securing Mobile Ad hoc Networks Using IoT

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Abstract

Mobile ad hoc networks are attaining popularity to its highest currently, as the users need wireless connectivity regardless of their geographical location. Threats of security attacks are growing on the Mobile Ad-hoc Networks (MANETs). MANETs must require a secure mode for communication and transmission which is rather challenging and vigorous issue. With the aim of providing secure transmission and communication, researcher worked explicitly on the security concerns in MANETs. Several secure protocols and security methods within the networks were projected but utmost of the security measures in their designs are not ruminated. Hence, a novel scheme is proposed in this paper for the secure and reliable data transmission in MANETs under black hole attack constructed on amended Ad hoc On-demand Multipath Distance Vector (AOMDV) protocol of our base scheme. This paper comprises AOMDV protocol for the multiple route discoveries along with K-Nearest Neighbor (KNN) for nearest neighbor node selection and use False key-build Advanced Encryption Standard (FAES) encryption scheme for cryptography method. FAES algorithm is used with the aim of securing the IoT devices and data from the hardware and network attacks. Also, the interaction of the scheme with the IoT based concepts making our work even smarter to the users. The proposed scheme performance is stable with higher throughput while that of base scheme. The quality of the proposed scheme is measured in terms of energy consumption, EE-delay and throughput. The results of simulation show that the Variance, EE-delay, energy consumption and throughput of proposed FAES-AOMDV protocol is lower than the original AOMDV protocol. FAES-AOMDV protocol ensures the secure transmission of data with least energy consumption in the presence of malicious nodes.

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References

  1. Devi, R., Sumathi, B., Gandhimathi, T., & Alaiyarasi, G. (2012). Performance metrics of MANET in multi-hop wireless ad hoc network routing protocols. In Proceedings of international journal of computational engineering research (IJCER), National Conference on Architecture, Software system and Green computing (pp. 1–6). ISSN: 2250-3005.

  2. Gupta, K., & Mittal, P. K. (2017). An overview of security in MANET. International Journals of Advanced Research in Computer Science and Software Engineering ISSN, 7, 2277–3128.

    Google Scholar 

  3. Sharma, S., & Gupta, A. K. (2013). A comprehensive review of security issues in manets. International Journal of Computer Applications, 69, 975–8887.

    Article  Google Scholar 

  4. Yu, W., & Köse, S. (2017). A lightweight masked AES implementation for securing IoT against CPA attacks. IEEE Transactions on Circuits and Systems I: Regular Papers, 64(11), 2934–2944.

    Article  MathSciNet  Google Scholar 

  5. Gurung, S., & Chauhan, S. (2019). A dynamic threshold based algorithm for improving security and performance of AODV under black-hole attack in MANET. Wireless Networks, 25(4), 1685–1695.

    Article  Google Scholar 

  6. Hurley-Smith, D., Wetherall, J., & Adekunle, A. (2017). SUPERMAN: Security using pre-existing routing for mobile ad hoc networks. IEEE Transactions on Mobile Computing, 16(10), 2927–2940.

    Article  Google Scholar 

  7. Rao, K. P. K., & Murugan, T. S. (2018). Energy efficient clustering technique using k-means and AODV-ACO Routing with Secured AES Cryptography in MANET. International Journal of Intelligent Engineering and Systems, 12(3), 292–302. https://doi.org/10.22266/ijies2019.0630.28.

  8. Khan, A., Sun, Q. T., Mahmood, Z., & Ghafoor, A. U. (2017). Energy efficient partial permutation encryption on network coded MANETs. Journal of Electrical and Computer Engineering, 2017, 4657831. https://doi.org/10.1155/2017/4657831.

  9. Pahlevanzadeh, H., Dofe, J., & Yu, Q. (2016). Assessing CPA resistance of AES with different fault tolerance mechanisms. In 2016 21st Asia and South Pacific design automation conference (ASP-DAC) (pp. 661–666). IEEE. https://doi.org/10.1109/ASPDAC.2016.7428087.

  10. Kumar, R., Tripathi, S., & Agrawal, R. (2018). A secure handshaking AODV routing protocol (SHS-AODV). In 2018 4th international conference on recent advances in information technology (RAIT) (pp. 1–5). IEEE. https://doi.org/10.1109/RAIT.2018.8389029.

  11. Singh, O., Singh, J., & Singh, R. (2018). Multi-level trust based intelligence intrusion detection system to detect the malicious nodes using elliptic curve cryptography in MANET. Cluster Computing, 21(1), 51–63.

    Article  Google Scholar 

  12. Abdel-Azim, M., Salah, H. E. D., & Eissa, M. E. (2018). IDS against black-hole attack for MANET. IJ Network Security, 20(3), 585–592.

    Google Scholar 

  13. Moudni, H., Er-rouidi, M., Mouncif, H., & El Hadadi, B. (2019). Black hole attack detection using fuzzy based intrusion detection systems in MANET. Procedia Computer Science, 151, 1176–1181.

    Article  Google Scholar 

  14. Sivanesh, S., & Dhulipala, V. S. (2020). Accurate and cognitive intrusion detection system (ACIDS): A novel black hole detection mechanism in mobile ad hoc networks. Mobile Networks and Applications, 1–9. https://doi.org/10.1007/s11036-019-01505-2.

  15. Borkar, G. M., & Mahajan, A. R. (2017). A secure and trust based on-demand multipath routing scheme for self-organized mobile ad-hoc networks. Wireless Networks, 23(8), 2455–2472.

    Article  Google Scholar 

  16. Reddy, A. P., & Satyanarayana, N. (2017). Energy-efficient stable multipath routing in MANET. Wireless Networks, 23(7), 2083–2091.

    Article  Google Scholar 

  17. Yadav, A. K., Das, S. K., & Tripathi, S. (2017). EFMMRP: Design of efficient fuzzy based multi-constraint multicast routing protocol for wireless ad-hoc network. Computer Networks, 118, 15–23.

    Article  Google Scholar 

  18. Das, S. K., & Tripathi, S. (2018). Intelligent energy-aware efficient routing for MANET. Wireless Networks, 24(4), 1139–1159.

    Article  Google Scholar 

  19. Muthurajkumar, S., Ganapathy, S., Vijayalakshmi, M., & Kannan, A. (2017). An intelligent secured and energy efficient routing algorithm for MANETs. Wireless Personal Communications, 96(2), 1753–1769.

    Article  Google Scholar 

  20. Selvi, P. T., & GhanaDhas, C. S. (2019). A novel algorithm for enhancement of energy efficient zone based routing protocol for MANET. Mobile Networks and Applications, 24(2), 307–317.

    Article  Google Scholar 

  21. van Glabbeek, R., Höfner, P., Portmann, M., & Tan, W. L. (2016). Modelling and verifying the AODV routing protocol. Distributed Computing, 29(4), 279–315.

    Article  MathSciNet  Google Scholar 

  22. Chavan, A. A., Kurule, D. S., & Dere, P. U. (2016). Performance analysis of AODV and DSDV routing protocol in MANET and modifications in AODV against black hole attack. Procedia Computer Science, 79, 835–844.

    Article  Google Scholar 

  23. Chelloug, S. A. (2015). Energy-efficient content-based routing in internet of things. Journal of Computer and Communications, 3(12), 9.

    Article  Google Scholar 

  24. Mishra, P., Gandhi, C., & Singh, B. (2017). An improved greedy forwarding scheme in MANETs. Journal of Telecommunications and Information Technology, 1–5.

  25. Muthukumaran, N. (2017). Analyzing throughput of MANET with reduced packet loss. Wireless Personal Communications, 97(1), 565–578.

    Article  Google Scholar 

  26. Elmahdi, E., Yoo, S. M., & Sharshembiev, K. (2020). Secure and reliable data forwarding using homomorphic encryption against blackhole attacks in mobile ad hoc networks. Journal of Information Security and Applications, 51, 102425.

    Article  Google Scholar 

  27. Pasupathi, S., Vimal, S., Harold-Robinson, Y., Khari, M., Verdú, E., & Crespo, R. G. (2020). Energy efficiency maximization algorithm for underwater Mobile sensor networks. Earth Science Informatics, 14(1), 1–11. https://doi.org/10.1007/s12145-020-00478-1.

  28. Khari, M. (2018). Wireless sensor networks: A technical survey. In Handbook of research on network forensics and analysis techniques (pp. 1–18). IGI Global. https://doi.org/10.4018/978-1-5225-4100-4.ch001.

  29. Jain, A., Khari, M., Verdu, E., Omatsu, S., & Crespo, R. G. (2020). A route selection approach for variable data transmission in wireless sensor networks. Cluster Computing-The Journal of Networks Software Tools And Applications, 23(3), 1697–1709. https://doi.org/10.1007/s10586-020-03115-0.

  30. Fabrice, S., & Fredrik, E. J. (2017). Detectionand preventionof malicious node based on node behaviour in manet. International Journal of Advanced Research In Computer Science, 8(9), 774–777.

    Article  Google Scholar 

  31. Pathan, M. S. C., & Kumar, M. V. (2016) A novel encryption scheme for providing security and energy efficiency in mobile ad hoc networks. In International conference on modern trends in engineering science and technology (ICMTEST 2016) (Vol. 2, No. 6, pp. 12–16).

  32. Bruzgiene, R., Narbutaite, L., & Adomkus, T. (2017). MANET network in internet of things system. Ad Hoc Networks, 89–114. https://doi.org/10.5772/66408.

  33. Robinson, Y. H., Vimal, S., Julie, E. G., Khari, M., Expósito-Izquierdo, C., & Martínez, J. (2020). Hybrid optimization routing management for autonomous underwater vehicle in the internet of underwater things. Earth Science Informatics, 14(1), 441–456. https://doi.org/10.1007/s12145-020-00538-6.

  34. Kumar, S., Solanki, V. K., Choudhary, S. K., Selamat, A., & González Crespo, R. (2020). Comparative study on ant colony optimization (ACO) and K-means clustering approaches for jobs scheduling and energy optimization model in Internet of Things (IoT). International Journal of Interactive Multimedia & Artificial Intelligence, 6(1), 1–10.

  35. Vimal, S., Khari, M., Crespo, R. G., Kalaivani, L., Dey, N., & Kaliappan, M. (2020). Energy enhancement using Multiobjective Ant colony optimisation with Double Q-learning algorithm for IoT based cognitive radio networks. Computer Communications, 154, 481–490.

    Article  Google Scholar 

  36. Singh, P., & Khari, M. (2021). Empirical analysis of energy-efficient hybrid protocol under black hole attack in MANETs. In Research in intelligent and computing in engineering (pp. 725–734). Singapore: Springer. https://doi.org/10.1007/978-981-15-7527-3_68.

  37. Priyadarshini, I., & Cotton, C. (2019). Internet memes: A novel approach to distinguish humans and bots for authentication. In Proceedings of the future technologies conference (pp. 204–222). Cham: Springer. https://doi.org/10.1007/978-3-030-32520-6_16.

  38. Priyadarshini, I., Wang, H., & Cotton, C. (2019). Some cyberpsychology techniques to distinguish humans and bots for authentication. In Proceedings of the future technologies conference (pp. 306–323). Cham: Springer. https://doi.org/10.1007/978-3-030-32523-7_21.

  39. Priyadarshini, I., & Puri, V. (2021). A convolutional neural network (CNN) based ensemble model for exoplanet detection. Earth Science Informatics, 14(2), 735–747.

  40. Priyadarshini, I., & Cotton, C. (2020). Intelligence in cyberspace: the road to cyber singularity. Journal of Experimental & Theoretical Artificial Intelligence, 1–35. https://doi.org/10.1080/0952813X.2020.1784296.

  41. Priyadarshini, I., & Cotton, C. (2021). A novel LSTM–CNN–grid search-based deep neural network for sentiment analysis. The Journal of Supercomputing, 1–22. https://doi.org/10.1007/s11227-021-03838-w.

  42. Priyadarshini, I., Mohanty, P. R., & Cotton, C. (2021). Analyzing some elements of technological singularity using regression methods. Comput Mater Contin, 67(3), 3229–3247.

    Google Scholar 

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Authors and Affiliations

  1. NSUT, East Campus, Delhi, India

    Priyanka Singh

  2. School of Computer and System Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Manju Khari

  3. Department of CSE, Ramco Institute of Technology, Rajapalayam, Tamilnadu, India

    S. Vimal

Authors
  1. Priyanka Singh
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  2. Manju Khari
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  3. S. Vimal
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Correspondence to Manju Khari.

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Singh, P., Khari, M. & Vimal, S. EESSMT: An Energy Efficient Hybrid Scheme for Securing Mobile Ad hoc Networks Using IoT. Wireless Pers Commun 126, 2149–2173 (2022). https://doi.org/10.1007/s11277-021-08764-x

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