Steganalysis of content adaptive and non adaptive spatial steganographic schemes in low volume payloads

Abstract

Steganography, a branch of data hiding technique aims to hide confidential newlineinformation within any digital media by obscuring the existence of hidden newlineinformation. the use of steganography for covert communication by fraudulent newlineentities poses a great threat to law enforcement agencies. on the contrary, newlinesteganalysis aims to detect steganography. the foremost purpose of steganalysis is newlineto determine whether or not a medium under suspicion is embedded with secret newlinedata. with the advent of recent steganographic algorithms, the process of cracking newlinethem has become very challenging for steganalysts. therefore, implementing newlineeffective and robust steganalysis techniques is a crucial task in this digital age to newlinecombat the ill effects of steganography.based on spatial least significant bit (lsb) steganography which is one of the most popular steganographic methods used with digital images, highly secure newlineand undetectable steganographic algorithms which embed secret in imperceptible newlinemanner are being developed. these algorithms resort to image content regions like newlinetextures to hide the secret payload. miniscule payloads are minute secret newlineinformation in the form of binary bits hidden inside any innocuously looking cover newlineimage for the purpose of undercover communication by steganography. detection newlineof such low volume payloads from a stego image is the very challenging task of newlinesteganalysis when there is no evidence of steganography method used. newlinethis dissertation addresses the above said challenges for developing newlinecompetent steganalyzers to tackle the problem of detection of spatial newlinesteganographic algorithms when embedding low volume payloads adaptive to newlineimage content regions as well as random lsbs directly in the pixels of image. the newlinemotto of this thesis is fourfold: to perform passive steganalysis that identifies newlinesuspicious image as cover or stego, to accomplish active steganalysis to detect newlinespecific steganographic scheme used, to implement quantitative steganalysis to newlineestimate payload length and location which leads to extraction of th