A Review of Enhancing Intrusion Detection Systems for Cybersecurity Using Artificial Intelligence (AI)

[1] Delamore B., Ko R.K.L. Chapter 9 - Security as a service (SecaaS)—An overview [Internet]. Ko R, Choo KKR, editors. ScienceDirect. Boston: Syngress; 2015 [cited 2023 May 15]. p. 187–203. Available from: https://www.sciencedirect.com/science/article/abs/pii/B9780128015957000094Search in Google Scholar

[2] Niksefat S., Kaghazgaran P., Sadeghiyan B. Privacy issues in intrusion detection systems: A taxonomy, survey and future directions. Computer Science Review. 2017 Aug;25:69–78.Search in Google Scholar

[3] Aljanabi M., Ismail M.A., Ali A.H. Intrusion Detection Systems, Issues, Challenges, and Needs. International Journal of Computational Intelligence Systems. 2021;Search in Google Scholar

[4] Aljanabi M., Ismail M.A., Ali A.H. Intrusion Detection Systems, Issues, Challenges, and Needs. International Journal of Computational Intelligence Systems. 2021;Search in Google Scholar

[5] Liao H.J., Richard Lin C.H., Lin Y.C., Tung K.Y. Intrusion detection system: A comprehensive review. Journal of Network and Computer Applications [Internet]. 2013 Jan;36(1):16–24. Available from: https://www.sciencedirect.com/science/article/pii/S1084804512001944Search in Google Scholar

[6] Cybersecurity Spotlight –Signature-Based vs Anomaly-Based Detection [Internet]. CIS. Available from: https://www.cisecurity.org/insights/spotlight/cybersecurity-spotlight-signature-based-vs-anomaly-based-detectionSearch in Google Scholar

[7] Repalle S, Ratnam Kolluru V. Intrusion Detection System using AI and Machine Learning Algorithm. International Research Journal of Engineering and Technology.Search in Google Scholar

[8] Li W., Yi P., Wu Y., Pan L., Li J. A New Intrusion Detection System Based on KNN Classification Algorithm in Wireless Sensor Network. Journal of Electrical and Computer Engineering [Internet]. 2014 [cited 2019 Nov 24];2014:1–8. Available from: https://www.hindawi.com/journals/jece/2014/240217/Search in Google Scholar

[9] Sommer R., Paxson V. Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. 2010 IEEE Symposium on Security and Privacy [Internet]. 2010 [cited 2019 Dec 6]; Available from: https://ieeexplore.ieee.org/ abstract/document/5504793/Search in Google Scholar

[10] Nobakht M., Sivaraman V., Boreli R. A Host-Based Intrusion Detection and Mitigation Framework for Smart Home IoT Using OpenFlow. 2016 11th International Conference on Availability, Reliability and Security (ARES). 2016 Aug;Search in Google Scholar

[11] Jagadish H.V., Gehrke J., Labrinidis A., Papakonstantinou Y., Patel J.M., Ramakrishnan R., et al. Big data and its technical challenges. Communications of the ACM. 2014 Jul 1;57(7):86–94.Search in Google Scholar

[12] Valdovinos I., Perez-Diaz J., Choo K.K., Botero J. Emerging DDoS attack detection and mitigation strategies in software-defined networks: Taxonomy, challenges and future directions. Journal of Network and Computer Applications [Internet]. 2021 Aug 1 [cited 2021 Sep 23];187:103093. Available from: https://www.sciencedirect.com/science/article/pii/S1084804521001156Search in Google Scholar

[13] Drewek-Ossowicka A., Pietrołaj M., Rumiński J. A survey of neural networks usage for intrusion detection systems. Journal of Ambient Intelligence and Humanized Computing. 2020 May 12;12(1):497–514.Search in Google Scholar

[14] Laghrissi F., Douzi S., Douzi K., Hssina B. IDS-attention: an efficient algorithm for intrusion detection systems using attention mechanism. Journal of Big Data. 2021 Nov 29;8(1).Search in Google Scholar

[15] Khraisat A., Gondal I., Vamplew P., Kamruzzaman J. Survey of intrusion detection systems: techniques, datasets and challenges. Cybersecurity [Internet]. 2019 Jul 17;2(1). Available from: https://cybersecurity.springeropen.com/articles/10.1186/s42400-019-0038-7Search in Google Scholar

[16] Otoum Y., Nayak A. AS-IDS: Anomaly and Signature Based IDS for the Internet of Things. Journal of Network and Systems Management. 2021 Mar 4;29(3).Search in Google Scholar

[17] Kim A., Park M., Lee D.H. AI-IDS: Application of Deep Learning to Real-Time Web Intrusion Detection. IEEE Access. 2020;8:70245–61.Search in Google Scholar

[18] Kanimozhi V., Jacob T.P. Artificial Intelligence based Network Intrusion Detection with hyper-parameter optimization tuning on the realistic cyber dataset CSE-CIC-IDS2018 using cloud computing. ICT Express. 2019 Apr;Search in Google Scholar

[19] William D. How AI can help improve intrusion detection systems [Internet]. GCN. Available from: https://gcn.com/cybersecurity/2020/04/how-ai-can-help-improve-intrusion-detection-systems/291266/Search in Google Scholar

[20] Fernández G., Xu S. A Case Study on Using Deep Learning for Network Intrusion Detection [Internet]. [cited 2023 May 15]. Available from: https://cspecc.utsa.edu/publications/files/Xu_2019_Case_Study_Deep_Learning_Net_Intr_Detect.pdfSearch in Google Scholar

[21] OpenAI. OpenAI [Internet]. OpenAI. 2019. Available from: https://openai.com/Search in Google Scholar

[22] tcpdump. TCPDUMP/LIBPCAP public repository. Tcpdumporg [Internet]. 2017; Available from: https://www.tcpdump.orgSearch in Google Scholar

[23] Dawson M., Bacius R., Gouveia L.B., & Vassilakos A. (2021). Understanding the challenge of cybersecurity in critical infrastructure sectors. Land Forces Academy Review, 26(1), 69-75.Search in Google Scholar