A Comparative Analysis of Signature-Based and Anomaly-Based Intrusion Detection Systems

Vasudev Karthik Ravindran, Sharad Shyam Ojha and Arvind Kamboj
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Vasudev Karthik Ravindran: Senior Software Development Engineer, Amazon, Seattle, WA, USA
Sharad Shyam Ojha: Software Development Manager, Amazon, Austin, United States
Arvind Kamboj: Department of Computer Science & Engineering, Shivalik College of Engineering, Dehradun

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 5, 209-214

Abstract: This paper presents a comprehensive comparative analysis of Signature-Based and Anomaly-Based Intrusion Detection Systems (IDS) using key performance metrics such as detection accuracy, false positive rate, adaptability to new threats, computational overhead, maintenance effort, scalability, and real-time performance. By examining these metrics, the study highlights the strengths and limitations of each IDS approach in handling both known and emerging cybersecurity threats. Signature-Based IDS demonstrates high accuracy and low false positives but struggles with adaptability and maintenance demands, while Anomaly-Based IDS offers better adaptability and threat detection versatility at the cost of increased false positives and resource consumption. The analysis emphasizes that an optimal IDS solution should consider the specific security needs and operational context of the deployment environment. The findings suggest that a hybrid approach, leveraging the complementary advantages of both techniques, can provide a more robust and resilient defense against the growing complexity of cyberattacks in modern networks.

Date: 2025
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