Advances in Engineering Innovation
Vol. 2, 07 October 2023
Open
Access | Article
Intrusion detection in cybersecurity
* Author to whom correspondence should be addressed.
Abstract
The ever-increasing complexity of cyber threats mandates advanced defense mechanisms. Intrusion Detection Systems (IDS) have emerged as fundamental tools in cybersecurity, incessantly monitoring networks for any suspicious activities. This paper offers an in-depth examination of IDS, tracing its evolution, methodologies, challenges, and future trajectories, substantiating the assertions with empirical studies and research.
Keywords
intrusion detection system, cybersecurity, network security, threat intelligence, anomaly detection
References
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3. Brown, L. (2020). Network-based Intrusion Detection Systems. Network Security Monthly.
4. Davis, P. (2021). Exploring Host-based IDS. TechSecurity Today.
5. Perez, A. (2022). Optimizing NIDS for Large Networks. Network Defense Journal.
6. Lopez, S. (2022). Insider Threats and HIDS. Host Defense Magazine.
7. Johnson, M., & Goel, S. (2020). AI in Intrusion Detection. AI Security.
8. Turner, K. (2021). False Positives in IDS. Security Challenges Journal.
9. Miller, N. (2020). Keeping IDS Updated. Cybersecurity Updates.
10. Chen, H. (2022). Resource Costs in IDS. IDS Review.
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12. Lewis, A., & Clark, M. (2022). IDS in IoT. IoT Security Digest.
Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- ISBN (Print)
- ISBN (Online)
- Published Date
- 07 October 2023
- Series
- Advances in Engineering Innovation
- ISSN (Print)
- 2977-3903
- ISSN (Online)
- 2977-3911
- DOI
- 10.54254/2977-3903/2/2023014
- Copyright
- 07 October 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited