Application of hypothesis testing theory for optimal detection of LSB matching data hiding

• Published in: Signal processing Vol. 93; no. 7; pp. 1724 - 1737
• Main Authors: Cogranne, Rémi, Retraint, Florent
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.07.2013; Elsevier
• Subjects: Applied sciences; Computer science; control theory; systems; Cryptography; Detectors; Digital; Digital media; Engineering Sciences; Exact sciences and technology; Hypothesis testing theory; Information forensics; Information hiding; Information, signal and communications theory; Matching; Mathematical analysis; Mathematical models; Mathematics; Memory and file management (including protection and security); Memory organisation. Data processing; Nuisance parameters; Optimal detection; Optimization; Probability and statistics; Sciences and techniques of general use; Signal and communications theory; Signal and Image processing; Signal processing; Software; State of the art; Statistics; Steganography and steganalysis; Telecommunications and information theory; Nuisance parameters; Information hiding; Hypothesis testing theory; Information forensics; Optimal detection; Steganography and steganalysis; Encapsulation; Multimedia; Statistical analysis; Nuisance parameter; Probabilistic approach; Software development; Forensic science; Measurement sensor; Local theory; Stéganography; Modeling; False alarm rate; Relevance; Hypothesis test; Cryptanalysis; Computer security
• ISSN: 0165-1684; 1872-7557
• DOI: 10.1016/j.sigpro.2013.01.014

This paper addresses the problem of detecting the presence of data hidden in digital media by the Least Significant Bit (LSB) matching scheme. In a theoretical context of known digital medium parameters, two important results are presented. First, the use of hypothesis testing theory allows the design of the Most Powerful (MP) test. Second, a study of the MP test provides the opportunity to analytically calculate its statistical properties in order to warrant a given probability of false-alarm. In practice when detecting LSB matching, the unknown medium parameters have to be estimated. Based on a local model of medium content, two different estimations which lead to two different tests are present. A numerical comparison with state-of-the-art detectors shows the good performance of the proposed tests and highlights the relevance of the proposed methodology. ► Steganalysis is addressed using hypothesis testing theory. ► The statistical performance of the proposed test is analytically calculated. ► The proposed test permits the guaranteeing of a false-alarm probability. ► This provides an upper bound on the detection performance of any detector. ► Using general statistical concept it can be applied for a wide range of media.