Ganavi M

Work place: CSE/JNNCE/Shivamogga, Karnataka



Research Interests: Information Security


Ganavi M is working as an Assistant Professor in the Department of Computer Science & Engineering (CSE) at Jawaharlal Nehru New College of Engineering (JNNCE), Shivamogga, Karnataka, India. She is pursuing a Ph.D. in Computer Science and Engineering from the Department of CSE, JNNCE, Shivamogga. Her research interests include Cryptography and information security.

Author Articles
An Efficient Image Steganography Scheme Using Bit-plane Slicing with Elliptic Curve Cryptography and Wavelet Transform

By Ganavi M Prabhudeva S Hemanth Kumar N P

DOI:, Pub. Date: 8 Aug. 2022

Information security is indispensable in the transmission of multimedia data. While accumulating and distributing such multimedia data, the access of data from a third person is the real security challenging issue. Information hiding plays an important role. Scramble the data before hiding it in carrier media gives enhanced security level for the data. In this paper, bit plane slicing is used to represent an input image with eight planes at bit-level instead of pixel-level. As the least significant bit contains noisy information, only the most significant bit plane can be used to represent an image. At the first level, an input image is processed through the spatial domain. Transform domain techniques are used to process the image at the middle level. Elliptic curve cryptography is used to scramble and descramble the MSB plane image. A logistic chaotic sequence of the input image is added to the most significant bit plane image to generate the final scrambled image. The discrete wavelet transform is used to embed the scrambled image in its high-frequency sub-bands. At the last level, a least significant bit technique, a spatial domain is used to embed the scrambled image in the carrier image. Message integrity is also verified by finding the hash of an input image. The performance of the proposed method is evaluated through various security measures. It gives good results as number of pixel change rate is closer to 100% and unified average changing intensity is 33.46.

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