IT Security and Intrusion Detection Systems: An Introduction

Year : 2024 | Volume :15 | Issue : 01 | Page : 10-17
By

    Seyfali Mahini

  1. Lecturer, Faculty of Computer Engineering, Islamic Azad University, Khoy Branch, Khoy, Iran

Abstract

This article deals with the current status of IT security in an industrialized country and one of the many approaches. The emphasis is on what are known as intrusion detection systems. These enable users to detect suspicious behavior and attacks in daily IT operations by analyzing data, resources, and network flows. Based on previous research, the different variants, available detection types, and their working methods are briefly explained and presented. The primary emphasis should be on understanding the functioning of the systems, their applications, and the constraints that govern them. The aim of the work is to select a suitable intrusion detection system for a hypothetical university such as SafeUni, its data center and the computer labs. This will be done after the mediation of the basics, an abbreviated requirements analysis is presented and the selected intrusion detection system, which best meets the requirements, is presented. The final stage involves summarizing the discovered information.

Keywords: IT security, intrusion detection system, host-based, network-based, hybrid systems, signature-based, anomaly-based

[This article belongs to Journal of Computer Technology & Applications(jocta)]

How to cite this article: Seyfali Mahini.IT Security and Intrusion Detection Systems: An Introduction.Journal of Computer Technology & Applications.2024; 15(01):10-17.
How to cite this URL: Seyfali Mahini , IT Security and Intrusion Detection Systems: An Introduction jocta 2024 {cited 2024 Apr 05};15:10-17. Available from: https://journals.stmjournals.com/jocta/article=2024/view=140176


References

  1. Jang-Jaccard J, Nepal S. A survey of emerging threats in cybersecurity. J Computer Syst Sci. 2014; 80 (5): 973–993.
  2. Brooks DJ, Coole MP. Intrusion detection systems. In: Shapiro LR, Maras M-H, editors. Encyclopedia of Security and Emergency Management. Cham, Switzerland: Springer International Publishing; 2021. pp. 490–494
  3. Khraisat A, Gondal I, Vamplew P, Kamruzzaman J. Survey of intrusion detection systems: techniques, datasets and challenges. Cybersecurity. 2019; 2 (1): 1–22.
  4. Kim K, Aminanto ME, Tanuwidjaja HC. Network Intrusion Detection Using Deep Learning: A Feature Learning Approach. New York, NY, USA: Springer; 2018.
  5. van Oorschot PC. Computer Security and the Internet. Cham, Switzerland: Springer International Publishing; 2020.
  6. Cid D, Hay A, Bray R. OSSEC Host-Based Intrusion Detection Guide. Burlington, MA, USA: Syngress; 2008.
  7. Kraft P, Weyert AG. Network Hacking: Professionelle Angriffs-und Verteidigungstechnikengegen Hacker und Datendiebe. Haar, Germany: Franzis Verlag; 2017.
  8. Shukla P, Kumar S. Learning Elastic Stack 7.0: Distributed Search, Analytics, and Visualization Using Elasticsearch, Logstash, Beats, and Kibana. Birmingham, UK: Packt Publishing Ltd; 2019.

Regular Issue Subscription Review Article
Volume 15
Issue 01
Received December 22, 2023
Accepted February 21, 2024
Published April 5, 2024