Hidden in Time, Revealed in Frequency: Spectral Features and Multiresolution Analysis for Encrypted Internet Traffic Classification

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent years, privacy and security concerns have led to the wide adoption of encrypted protocols, making encrypted traffic a major portion of overall communications online. The transition into more secure protocols poses significant challenges for internet service providers to utilize traditional traffic classification techniques in order to guarantee the Quality of Service (QoS), Quality of Experience (QoE), and cyber-security of their customers. In this work, we introduce two methods, namely STFT-TC and DWT-TC, leveraging compact time-series representation coupled with well-known techniques from the field of Digital Signal Processing (DSP): the short-time Fourier transform (STFT) and the discrete wavelet transform (DWT). The STFT-TC method extracts a suite of statistical and spectral features from the magnitude spectrogram, offering a fresh perspective on interpreting and classifying encrypted traffic. The DWT-TC method extracts statistical features from the wavelet coefficients and incorporates unique characteristics that describe the signal's shape and energy distribution. Evaluating our methods on two public QUIC datasets demonstrated improvements in accuracy of up to 5.7%. Similarly, the F1-scores also showed enhancements, with increments of up to 5.9% for the same datasets.

Original languageEnglish
Title of host publication2024 IEEE 21st Consumer Communications and Networking Conference, CCNC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages266-271
Number of pages6
ISBN (Electronic)9798350304572
DOIs
StatePublished - 2024
Event21st IEEE Consumer Communications and Networking Conference, CCNC 2024 - Las Vegas, United States
Duration: 6 Jan 20249 Jan 2024

Publication series

NameProceedings - IEEE Consumer Communications and Networking Conference, CCNC
ISSN (Print)2331-9860

Conference

Conference21st IEEE Consumer Communications and Networking Conference, CCNC 2024
Country/TerritoryUnited States
CityLas Vegas
Period6/01/249/01/24

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