Comprehensive Review of Network Intrusion Detection and Prevention Systems

Article Sidebar

Main Article Content

Ms. Hemangni Mehta
Ms. Anjali Nizama
Ms. Subhashini K
Abstract— The global network infrastructure remains vulnerable and is susceptible to attacks from various sources. These attacks can take the form of denial-of-service (DoS) or other malicious threats. To safeguard such networks, Intrusion Detection and Prevention Systems (IDPS) are employed. These systems serve as critical security mechanisms designed to detect and prevent both internal and external threats.IDPS continuously monitor network traffic using a variety of techniques. When suspicious or malicious activity is detected, the system blocks the threat and generates alerts for further investigation. Intrusion remains a significant challenge, especially in hybrid computing environments.This paper explores key concepts including network intrusion, types of intrusions, intrusion detection systems, and a review of previous research related to IDPS. The software solutions implemented to counter such threats are referred to as intrusion prevention systems (IPS). Various types of prevention systems are discussed within this study.
Comprehensive Review of Network Intrusion Detection and Prevention Systems. (2025). International Journal of Latest Technology in Engineering Management & Applied Science, 14(6), 804-807. https://doi.org/10.51583/IJLTEMAS.2025.140600087

Downloads

References

Yashashree Dawle, Manasi Naik,Sumedha Vande,Nikita Zarkar ,”Reserch of Database Security Using Intrusion Detection System” International Journal of Latest Engineering Research and Applications (IJLERA) ISSN: 2455-7137 Volume – 02, Issue – 03, March – 2017, PP – 01-06.

Janu Gupta, Jasbir Singh” Detecting Anomaly Based Network Intrusion Using Feature Extraction and Classification Techniques” International Journal of Advanced Research in Computer Science,volume 8, No. 5, May – June 2017.

Atmaja Sahasrabuddhe, Sonali Naikade, Akshaya Ramaswamy, Burhan Sadliwala , Prof.Dr.Pravin Futane,” Survey on Intrusion Detection System using Data Mining Techniques, International Research Journal of Engineering and Technology (IRJET)Volume:04 Issue: 05 May -2017 .

Kanubhai K. Patel, Bharat V. Buddhadev”Research of An Architecture of Hybrid Intrusion Detection System” International Journal of Information & Network Security (IJINS) Vol.2, No.2, April 2013, pp. 197~202.

Amaan Anwar & Syed Imtiyaz Hassan,” Applying Artificial Intelligence Techniques to Prevent Cyber Assaults “International Journal of Computational Intelligence Research ISSN 0973-1873 Volume 13, Number 5 (2017), pp.

Ghosh, A. Shinde, and N. Pissinou, “A Survey on Network Intrusion Detection using Deep Learning Techniques,” IEEE Access, vol. 9, pp. 21932–21957, 2021. DOI: 10.1109/ACCESS.2021.3056066

B. Subba, S. Biswas, and S. K. Das, “A Neural Network- Based System for Intrusion Detection and Attack Classification,” Computer Communications, vol. 145, pp. 167–175, Nov. 2019.

DOI: 10.1016/j.comcom.2019.07.006

M. Usama et al., “Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges,” IEEE Access, vol. 7, pp. 65579–65615, 2019. DOI: 10.1109/ACCESS.2019.2916648

S. Shone and Q. N. Ng, “A Deep Learning Approach to Network Intrusion Detection,” IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 2, no. 1, pp. 41–50, Feb. 2018.DOI: 10.1109/TETCI.2017.2772792

S. B. Jadhav and A. R. Thakare, “Anomaly Detection for Network Intrusion Prevention: A Hybrid Approach,” Procedia Computer Science, vol. 167, pp. 719–728, 2020. DOI: 10.1016/j.procs.2020.03.387

Article Details

How to Cite

Comprehensive Review of Network Intrusion Detection and Prevention Systems. (2025). International Journal of Latest Technology in Engineering Management & Applied Science, 14(6), 804-807. https://doi.org/10.51583/IJLTEMAS.2025.140600087