References
- S. Tanzeel Shah, B. Shams and S. Khan, “A Survey on Secure Routing in Wireless Sensor Networks.” International Journal of Sensors Wireless Communications and Control, 3, no. 1, pp. 37-44, 2013.
- T. Delwar, U. Aras, S. Mukhopadhyay, A. Kumar, U. Kshirsagar, Y. Lee, M. Singh and J. Ryu, “The Intersection of Machine Learning and Wireless Sensor Network Security for Cyber-Attack Detection: A Detailed Analysis.” Sensors, 24, no. 19, pp. 6377, 2024.
- M. Hassan, M. Mohamad and F. Muchtar, “Advanced Intrusion Detection in MANETs: A Survey of Machine Learning and Optimization Techniques for Mitigating Black/Gray Hole Attacks.” IEEE Access, 2024.
- D. Boubiche and A. Bilami, “Cross layer intrusion detection system for wireless sensor network.” International Journal of Network Security & Its Applications, 4, no. 2, pp. 35, 2012.
- F. Catak and A. Mustacoglu, “Distributed denial of service attack detection using autoencoder and deep neural networks.” Journal of Intelligent & Fuzzy Systems, 37, no. 3, pp. 3969-3979, 2019.
- M. Asad, M. Asim, T. Javed, M. Beg, H. Mujtaba and S. Abbas, “Deepdetect: detection of distributed denial of service attacks using deep learning.” The Computer Journal, 63, no. 7, pp. 983-994, 2020.
- B. Sahoo and A. Sabyasachi, “A Metaheuristic Algorithm Based Clustering Protocol for Energy Harvesting in IoT-Enabled WSN.” Wireless Personal Communications, pp. 1-26, 2024.
- A. Bozorgchenani, M. Jahanshahi and D. Tarchi, “Gateway selection and clustering in multi‐interface wireless mesh networks considering network reliability and traffic.” Transactions on Emerging Telecommunications Technologies, 29, no. 3, pp. e3215, 2018.
- B. Sahoo, H. Pandey and T. Amgoth, “A genetic algorithm inspired optimized cluster head selection method in wireless sensor networks.” Swarm and Evolutionary Computation, 75, pp. 101151, 2022.
- A. Nanda, P. Nanda, X. He, A. Jamdagni and D. Puthal, “A hybrid encryption technique for Secure-GLOR: The adaptive secure routing protocol for dynamic wireless mesh networks.” Future Generation Computer Systems, 109, pp. 521-530, 2020.
- K. Haseeb, A. Almogren, N. Islam, I. Din and Z. Jan, “An energy-efficient and secure routing protocol for intrusion avoidance in IoT-based WSN.” Energies, 12, no. 21, pp. 4174, 2019.
- M. Nasir, S. Khan, M. Khan and M. Fatima, “Swarm intelligence inspired intrusion detection systems—a systematic literature review.” Computer Networks, 205, pp. 108708, 2022.
- S. Pingale and S. Sutar, “Remora whale optimization-based hybrid deep learning for network intrusion detection using CNN features.” Expert Systems with Applications, 210, pp. 118476, 2022.
- A. Alqahtani, “RETRACTED ARTICLE: FSO-LSTM IDS: hybrid optimized and ensembled deep-learning network-based intrusion detection system for smart networks.” The Journal of Supercomputing 78, no. 7, pp. 9438-9455, 2022.
- E. Bernardino, A. Bernardino, J. Sánchez-Pérez, J. Pulido and M. Rodríguez, “Swarm optimisation algorithms applied to large balanced communication networks.” Journal of network and computer applications, 36, no. 1, pp. 504-522, 2013.
- DDoS Evaluation Dataset CICDDoS2019. https://www.unb.ca/cic/datasets/ddos-2019.html (2019). Accessed 10 Jun 2020.
- F. Al-Anzi, “Design and analysis of intrusion detection systems for wireless mesh networks.” Digital Communications and Networks 8, no. 6, pp. 1068-1076, 2022.
- S. Mahadik, P. Pawar and R. Muthalagu, “Efficient intelligent intrusion detection system for heterogeneous internet of things (HetIoT).” Journal of Network and Systems Management, 31, no. 1, pp. 2, 2023.
- D. Sharma, S. Dhurandher, S. Kumaram, K. Gupta and P. Sharma, “Mitigation of black hole attacks in 6LoWPAN RPL-based Wireless sensor network for cyber physical systems.” Computer Communications, 189, pp. 182-192, 2022.
- B. Bhati and C. Rai, “Analysis of support vector machine-based intrusion detection techniques.” Arabian Journal for Science and Engineering 45, no. 4, pp. 2371-2383, 2020.
- L. Gandhimathi and G. Murugaboopathi, “A novel hybrid intrusion detection using flow-based anomaly detection and cross-layer features in wireless sensor network.” Automatic Control and Computer Sciences, 54, no. 1, pp. 62-69, 2020.
- L. Gandhimathi and G Murugaboopathi, “Cross layer intrusion detection and prevention of multiple attacks in Wireless Sensor Network using Mobile agent.” In 2016 International Conference on Information Communication and Embedded Systems (ICICES), pp. 1-5. IEEE, 2016.
- S. Ramesh, C. Yaashuwanth, K. Prathibanandhi, A. Basha and T. Jayasankar, “An optimized deep neural network-based DoS attack detection in wireless video sensor network.” Journal of Ambient Intelligence and Humanized Computing, pp. 1-14, 2021.
- G. Liu, H. Zhao, F. Fan, G. Liu, Q. Xu and S. Nazir, “An enhanced intrusion detection model based on improved kNN in WSNs.” Sensors 22, no. 4, pp. 1407, 2022.
- V. Borgiani, P. Moratori, J. Kazienko, E. Tubino and S. Quincozes, “Toward a distributed approach for detection and mitigation of denial-of-service attacks within industrial internet of things.” IEEE Internet of Things Journal 8, no. 6, pp. 4569-4578, 2020.
- R. Vijayanand and D. Devaraj, “A novel feature selection method using whale optimization algorithm and genetic operators for intrusion detection system in wireless mesh network.” IEEE Access, 8, pp. 56847-56854, 2020.
- R. Thillaikarasi and S. Bhanu, “Adaptive DSR to mitigate packet dropping attacks in WMNs using cross layer metrics.” Journal of Ambient Intelligence and Humanized Computing, pp. 1-17, 2021.
- M. Assis, L. Carvalho, J. Rodrigues, J. Lloret and M. Proença Jr, “Near real-time security system applied to SDN environments in IoT networks using convolutional neural network.” Computers & Electrical Engineering, 86, pp. 106738, 2020.
- K. Pal and K. Sudeep, “Preprocessing for image classification by convolutional neural networks.” In 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp. 1778-1781. IEEE, 2016.
- K. Ghori, M. Imran, A. Nawaz, R. Abbasi, A. Ullah and L. Szathmary, “Performance analysis of machine learning classifiers for non-technical loss detection.” Journal of Ambient Intelligence and Humanized Computing, pp. 1-16, 2023.
- C. Pontes, M. Souza, J. Gondim, M. Bishop and M. Marotta, “A new method for flow-based network intrusion detection using the inverse Potts model.” IEEE Transactions on Network and Service Management 18, no. 2. pp. 1125-1136, 2021.
- M. Wani, F. Bhat, S. Afzal, A. Khan, M. Wani, F. Bhat, S. Afzal and A. Khan, “Training supervised deep learning networks.” Advances in Deep Learning, pp. 31-52, 2020.
- S. Indolia, A. Goswami, S. Mishra and P. Asopa, “Conceptual understanding of convolutional neural network-a deep learning approach.” Procedia computer science, 132, pp. 679-688, 2018.
- D. Kingma, “Adam: A method for stochastic optimization.” arXiv preprint arXiv:1412.6980, 2014.
- A. Taqi, A. Awad, F. Al-Azzo and M. Milanova, “The impact of multi-optimizers and data augmentation on TensorFlow convolutional neural network performance.” In 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), pp. 140-145. IEEE, 2018.
- V. Gowdhaman and R. Dhanapal, “An intrusion detection system for wireless sensor networks using deep neural network.” Soft Computing, 26, no. 23, pp. 13059-13067, 2022.
- I. Almomani, B. Al-Kasasbeh and M. Al-Akhras, “WSN‐DS: a dataset for intrusion detection systems in wireless sensor networks.” Journal of Sensors, 2016, no. 1, pp. 4731953, 2016.
- S. Naser, Y. Ali and D. OBE, “Deep learning model for cyber-attacks detection method in wireless sensor networks.” Periodicals of Engineering and Natural Sciences (PEN), 10, no. 2, pp. 251-259, 2022.
- M. Maheswari and R. Karthika, “A Novel hybrid deep learning framework for intrusion detection systems in WSN-IoT networks.” Intelligent Automation & Soft Computing, 33, no. 1, pp. 365-382, 2022.
- A. Gankotiya, V. Kumar and K. Vaisla, “Building IPv6 addressing scheme using Hybrid Duplicate Address Detection to prevent Denial of Service Attack.” Computers and Electrical Engineering, 117, pp. 109229, 2024.
- M. Premkumar and T. Sundararajan, “Defense countermeasures for DoS attacks in WSNs using deep radial basis networks.” Wireless Personal Communications, 120, no. 4, pp. 2545-2560, 2021.