A Hybrid Entropy-Rate Analysis Framework for Lightweight DDoS Detection in Modern Networks
Abstract: Distributed Denial-of-Service (DDoS) attacks continue to undermine the stability of modern networks by overwhelming servers and critical services with artificially generated traffic. This work proposes a lightweight hybrid entropy- rate detection framework capable of identifying both high-volume and stealthy low-rate attacks. The approach combines short-term statistical indicators- such as source-IP entropy, packet-rate deviation, byte-volume behavior- and temporal correlation into a unified anomaly-scoring model. By correlating rapid distributional shifts with rate anomalies and temporal persistence, the method enables early detection of diverse attack types while remaining computationally efficient for deployment in resource-constrained institutional networks.
Keywords: DDoS mitigation, entropy-based analysis, traffic-rate deviation, anomaly detection, lightweight IDS, network security
How to Cite?: Santhosh K. M., "A Hybrid Entropy-Rate Analysis Framework for Lightweight DDoS Detection in Modern Networks", Volume 11 Issue 11, November 2022, International Journal of Science and Research (IJSR), Pages: 1564-1567, https://www.ijsr.net/getabstract.php?paperid=SR221120164006, DOI: https://dx.doi.org/10.21275/SR221120164006