Binary Coded Genetic Algorithm with Ensemble Classifier for feature selection in JPEG steganalysis

Vasily Sachnev, Hyoung Joong Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this paper, we propose a Binary Coded Genetic Algorithm with Ensemble Classification feature selection procedure designed for steganalysis. Proposed feature selection method was used for searching the most appropriate subset of features from 22510 dimension feature space superior for JPEG steganal-ysis. Reduced set of features shows better classification accuracy for JPEG steganalysis compared to complete set of features. In our method we used an ensemble classifier to approximate the functional relationship between the reduced feature set and class label. Search for optimal subset of features requires to solve two optimization problems: define the optimal number of features and define the optimal subset itself. Proposed Binary Coded Genetic algorithm enables to solve two optimization problems together. Each feature is coded as a binary coefficient in a binary string, which represent one solution of the feature selection problem. Genetic operations executed for binary strings (parents) results new binary strings (child) with good chance to have higher classification accuracy for JPEG steganalysis. Experimental results clearly indicate the advantage of using the proposed reduced set of features for JPEG steganalysis.

Original languageEnglish
Title of host publicationIEEE ISSNIP 2014 - 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Conference Proceedings
PublisherIEEE Computer Society
ISBN (Print)9781479928439
DOIs
Publication statusPublished - 2014 Jan 1
Event9th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, IEEE ISSNIP 2014 - Singapore, Singapore
Duration: 2014 Apr 212014 Apr 24

Other

Other9th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, IEEE ISSNIP 2014
CountrySingapore
CitySingapore
Period14/4/2114/4/24

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Sachnev, V., & Kim, H. J. (2014). Binary Coded Genetic Algorithm with Ensemble Classifier for feature selection in JPEG steganalysis. In IEEE ISSNIP 2014 - 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Conference Proceedings [6827700] IEEE Computer Society. https://doi.org/10.1109/ISSNIP.2014.6827700