Fast Audio Codec Identification Using Overlapping LCS

TL;DR

This paper introduces a fast and accurate audio codec identification method based on overlapped LCS features, significantly improving speed while maintaining high accuracy in packet classification.

Contribution

It presents a novel overlapped LCS-based feature extraction technique that enhances speed and accuracy in audio codec identification over traditional methods.

Findings

Achieved 97% accuracy with 8 KB packets

Method is eight times faster than traditional LCS extraction

Overlapping packet division does not reduce accuracy

Abstract

Audio data are widely exchanged over telecommunications networks. Due to the limitations of network resources, these data are typically compressed before transmission. Various methods are available for compressing audio data. To access such audio information, it is first necessary to identify the codec used for compression. One of the most effective approaches for audio codec identification involves analyzing the content of received packets. In these methods, statistical features extracted from the packets are utilized to determine the codec employed. This paper proposes a novel method for audio codec classification based on features derived from the overlapped longest common sub-string and sub-sequence (LCS). The simulation results, which achieved an accuracy of 97% for 8 KB packets, demonstrate the superiority of the proposed method over conventional approaches. This method divides each 8 KB packet into fifteen 1 KB packets with a 50% overlap. The results indicate that this division has no significant impact on the simulation outcomes, while significantly speeding up the feature extraction, being eight times faster than the traditional method for extracting LCS features.