N-Gram against the Machine: On the Feasibility of the N-Gram Network Analysis for Binary Protocols

Abstract

In recent years we have witnessed several complex and high-impact attacks specifically targeting “binary” protocols (RPC, Samba and, more recently, RDP). These attacks could not be detected by current – signature-based – detection solutions, while – at least in theory – they could be detected by state-of-the-art anomaly-based systems. This raises once again the still unanswered question of how effective anomaly-based systems are in practice. To contribute to answering this question, in this paper we investigate the effectiveness of a widely studied category of network intrusion detection systems: anomaly-based algorithms using n-gram analysis for payload inspection. Specifically, we present a thorough analysis and evaluation of several detection algorithms using variants of n-gram analysis on real-life environments. Our tests show that the analyzed systems, in presence of data with high variability, cannot deliver high detection and low false positive rates at the same time.

Emmanuele Zambon

Assistant Professor

My research interests include Industrial Control System security and network intrusion detection.