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Active research is going on to securely transmit a secret message orso-called steganography by using data-hiding techniques in digital images.After assessing the state-of-the-art research work, we found, most of theexisting solutions are not promising and are ineffective against machinelearning-based steganalysis. In this paper, a lightweight steganography schemeis presented through graphical key embedding and obfuscation of data throughencryption. By keeping a mindset of industrial applicability, to show theeffectiveness of the proposed scheme, we emphasized mainly deep learning-basedsteganalysis. The proposed steganography algorithm containing two schemeswithstands not only statistical pattern recognizers but also machine learningsteganalysis through feature extraction using a well-known pre-trained deeplearning network Xception. We provided a detailed protocol of the algorithm fordifferent scenarios and implementation details. Furthermore, differentperformance metrics are also evaluated with statistical and machine learningperformance analysis. The results were quite impressive with respect to thestate of the arts. We received 2.55% accuracy through statistical steganalysisand machine learning steganalysis gave maximum of 49.93~50% correctlyclassified instances in good condition.

An Efficient Light-weight LSB steganography with Deep learning Steganalysis