Rajeev K. currently serves as Research Associate at TIFAC-CORE in Cyber Security. His areas of research include Boolea functions, Steganography, Visual Cryptography, Pairing based cryptography.

Qualification: M. Sc. in Mathematics (Calicut University)


Publication Type: Book Chapter

Year of Publication Title


P. P. Amritha, Induja, K., and Rajeev, K., “Active Warden Attack on Steganography Using Prewitt Filter”, in Proceedings of the International Conference on Soft Computing Systems: ICSCS 2015, Volume 2, P. L. Suresh and Panigrahi, K. Bijaya, Eds. New Delhi: Springer India, 2016, pp. 591–599.[Abstract]

Digital Steganography is a method used to embed secret message in digital images. Attackers make use of steganographic method for the purpose of transmitting malicious messages. In this paper, we proposed active warden method by using Prewitt filter on the input image to highlight the edge locations. Then the Discrete Spring Transform (DST) is applied on the filtered image to relocate the pixel location so that secret message cannot be recovered. This method is a generic method since it is independent of the steganography algorithms used and it does not require any training sets. We have compared our results with the existing system which used Sobel filter and curve length method. Our experimental results concluded that Prewitt was able to destroy the message to larger extent than by using Sobel filter and curve length method. Bit error rate (BER) and PSNR was used to measure the performance of our system. Our method was able to preserve the perceptual quality of the image. More »»


P. P. Amritha, M. Muraleedharan, S., Rajeev, K., and Dr. M. Sethumadhavan, “Steganalysis of LSB Using Energy Function”, in Intelligent Systems Technologies and Applications: Volume 1, S. Berretti, M. Thampi, S., and Srivastava, R. Praveen, Eds. Cham: Springer International Publishing, 2016, pp. 549–558.[Abstract]

This paper introduces an approach to estimate energy of pixel associated with its neighbors. We define an energy function of a pixel which replaces the pixel value by mean or median value of its neighborhood. The correlations inherent in a cover signal can be used for steganalysis, i.e, detection of presence of hidden data. Because of the interpixel dependencies exhibited by natural images this function was able to differentiate between cover and stego image. Energy function was modeled using Gibbs distribution even though pixels in an image have the property of Markov Random Field. Our method is trained to specific embedding techniques and has been tested on different textured images and is shown to provide satisfactory result in classifying cover and stego using energy distribution. More »»