Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/4649
Title: BitCoding: Protocol type agnostic robust bit level signatures for traffic classification
Authors: Hubballi, Neminath
Swarnkar, Mayank
Keywords: Chemical detection;Classification (of information);Digital storage;Application protocols;Application signatures;Binary protocols;Cross evaluation;Network applications;Run-length coding;Signature-matching;Traffic classification;Network security
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Hubballi, N., & Swarnkar, M. (2017). BitCoding: Protocol type agnostic robust bit level signatures for traffic classification. Paper presented at the 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings, , 2018-January 1-6. doi:10.1109/GLOCOM.2017.8254001
Abstract: Traffic classification has received considerable interest as many network applications use obfuscation methods to hide their identity and bypass security. Traditionally application signatures are generated using byte level content of application flows. Increasingly new data formats are used to encode the application protocols which render the byte level signatures ineffective in identifying applications. To address this issue we propose BitCoding a bit-level application signature generation using invariant bits of application flows. Unlike other works, BitCoding uses only a small number of initial bits of flows to generate signature and signature bits are encoded using run length coding to reduce size; hence it is very inexpensive in storage and is light weight for signature matching. We evaluate BitCoding using three different datasets and show that it is able to classify both text based and binary protocols with high accuracy, making it protocol type agnostic. Further we perform cross evaluation of signatures generated to understand the portability of signatures generated to other sites and conclude that it will lead to a small compromise in the detection rate. © 2017 IEEE.
URI: https://doi.org/10.1109/GLOCOM.2017.8254001
https://dspace.iiti.ac.in/handle/123456789/4649
ISBN: 9781509050192
Type of Material: Conference Paper
Appears in Collections:Department of Computer Science and Engineering

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