Trends in Interpretable and Lightweight Intrusion Detection Systems: A Bibliometric Analysis of Network Traffic Anomaly Detection - Elkaf Pramudya; Ratih Hafsarah Maharrani; Abdussalam Abdussalam; Wildanil Ghozi (P3M Politeknik Negeri Cilacap, 2026)
This study examines recent developments in interpretable and lightweight Intrusion Detection Systems (IDS) through a bibliometric analysis of 399 publications on network traffic anomaly detection from 2019 to 2025. Using a structured workflow comprising data collection, filtering, topic categorization, and visualization, the analysis reveals a significant increase in IDS-related publications, rising from fewer than 20 papers per year before 2019 to over 200 in 2025, reflecting growing interest in efficient and transparent security solutions. Topic categorization identifies IDS as the dominant research area, followed by Lightweight approaches, Anomaly Detection, IoT, and Explainability, with minimal contributions from other topics. Citation patterns confirm IDS and lightweight methods as the most influential themes. Journal analysis highlights Applied Sciences, Electronics, and IEEE Access as the leading publication venues. Overall, the findings indicate a clear shift toward IDS research emphasizing low computational cost, practical deployment, and model transparency, while also underscoring the ongoing need for unified benchmarks, realistic datasets, and evaluation frameworks to support broader adoption of interpretable and lightweight IDS technologies.