Subject Areas : Machine learning
Heshamt Asadi
1
,
Mahmood Alborzi
2
,
Hessam Zandhessami
3
1 -
2 -
3 -
Keywords:
Abstract :
[1] H. Nandanwar and R. Katarya, “Deep learning enabled intrusion detection system for Industrial IOT environment,” Expert Syst Appl, vol. 249, p. 123808, Sep. 2024, doi: 10.1016/j.eswa.2024.123808.
[2] M. F. Elrawy, A. I. Awad, and H. F. A. Hamed, “Intrusion detection systems for IoT-based smart environments: a survey,” Journal of Cloud Computing, vol. 7, no. 1, p. 21, Dec. 2018, doi: 10.1186/s13677-018-0123-6.
[3] A. Kaushik and H. Al-Raweshidy, “A novel intrusion detection system for internet of things devices and data,” Wireless Networks, vol. 30, no. 1, pp. 285–294, Jan. 2024, doi: 10.1007/s11276-023-03435-0.
[4] S. Alosaimi and S. M. Almutairi, “An Intrusion Detection System Using BoT-IoT,” Applied Sciences, vol. 13, no. 9, p. 5427, Apr. 2023, doi: 10.3390/app13095427.
[5] V. Choudhary, S. Tanwar, and T. Choudhury, “Evaluation of contemporary intrusion detection systems for internet of things environment,” Multimed Tools Appl, vol. 83, no. 3, pp. 7541–7581, Jan. 2024, doi: 10.1007/s11042-023-15918-5.
[6] A. Awajan, “A Novel Deep Learning-Based Intrusion Detection System for IoT Networks,” Computers, vol. 12, no. 2, p. 34, Feb. 2023, doi: 10.3390/computers12020034.
[7] R. Chaganti, W. Suliman, V. Ravi, and A. Dua, “Deep Learning Approach for SDN-Enabled Intrusion Detection System in IoT Networks,” Information, vol. 14, no. 1, p. 41, Jan. 2023, doi: 10.3390/info14010041.
[8] E. Anthi, L. Williams, M. Slowinska, G. Theodorakopoulos, and P. Burnap, “A Supervised Intrusion Detection System for Smart Home IoT Devices,” IEEE Internet Things J, vol. 6, no. 5, pp. 9042–9053, Oct. 2019, doi: 10.1109/JIOT.2019.2926365.
[9] T. Saba, A. Rehman, T. Sadad, H. Kolivand, and S. A. Bahaj, “Anomaly-based intrusion detection system for IoT networks through deep learning model,” Computers and Electrical Engineering, vol. 99, p. 107810, Apr. 2022, doi: 10.1016/j.compeleceng.2022.107810.
[10] M. Almiani, A. AbuGhazleh, A. Al-Rahayfeh, S. Atiewi, and A. Razaque, “Deep recurrent neural network for IoT intrusion detection system,” Simul Model Pract Theory, vol. 101, p. 102031, May 2020, doi: 10.1016/j.simpat.2019.102031.
[11] A. Heidari and M. A. Jabraeil Jamali, “Internet of Things intrusion detection systems: a comprehensive review and future directions,” Cluster Comput, vol. 26, no. 6, pp. 3753–3780, Dec. 2023, doi: 10.1007/s10586-022-03776-z.
[12] D. Musleh, M. Alotaibi, F. Alhaidari, A. Rahman, and R. M. Mohammad, “Intrusion Detection System Using Feature Extraction with Machine Learning Algorithms in IoT,” Journal of Sensor and Actuator Networks, vol. 12, no. 2, p. 29, Mar. 2023, doi: 10.3390/jsan12020029.
[13] A. Kumar, K. Abhishek, M. R. Ghalib, A. Shankar, and X. Cheng, “Intrusion detection and prevention system for an IoT environment,” Digital Communications and Networks, vol. 8, no. 4, pp. 540–551, Aug. 2022, doi: 10.1016/j.dcan.2022.05.027.
[14] S. U. Jan, S. Ahmed, V. Shakhov, and I. Koo, “Toward a Lightweight Intrusion Detection System for the Internet of Things,” IEEE Access, vol. 7, pp. 42450–42471, 2019, doi: 10.1109/ACCESS.2019.2907965.
[15] H. Alazzam, A. Sharieh, and K. E. Sabri, “A feature selection algorithm for intrusion detection system based on Pigeon Inspired Optimizer,” Expert Syst Appl, vol. 148, p. 113249, Jun. 2020, doi: 10.1016/j.eswa.2020.113249.
[16] R. Zhao et al., “A Novel Intrusion Detection Method Based on Lightweight Neural Network for Internet of Things,” IEEE Internet Things J, vol. 9, no. 12, pp. 9960–9972, 2022, doi: 10.1109/JIOT.2021.3119055.
[17] S. M. Kasongo, “A deep learning technique for intrusion detection system using a Recurrent Neural Networks based framework,” Comput Commun, vol. 199, pp. 113–125, Feb. 2023, doi: 10.1016/j.comcom.2022.12.010.
[18] V. Hnamte, H. Nhung-Nguyen, J. Hussain, and Y. Hwa-Kim, “A Novel Two-Stage Deep Learning Model for Network Intrusion Detection: LSTM-AE,” IEEE Access, vol. 11, pp. 37131–37148, 2023, doi: 10.1109/ACCESS.2023.3266979.
