Qualification: 
M.Tech
pp_amritha@cb.amrita.edu

Amrita P. P. currently serves as Assistant Professor at TIFAC-CORE in Cyber Security, Coimbatore Campus. 

Publications

Publication Type: Journal Article

Year of Publication Publication Type Title

2017

Journal Article

P. P. Amritha, Ravi, R. P., and Dr. M. Sethumadhavan, “Active steganalysis on svd-based embedding algorithm”, Advances in Intelligent Systems and Computing, vol. 515, pp. 777-785, 2017.[Abstract]


Steganography is an art of hiding of secret information in an innocuous medium like an image. Most of the current steganographic algorithms hide data in the spatial or transform domain. In this paper, we perform attacks on three singular value decomposition-based spatial steganographic algorithms, by applying image processing operations. By performing these attacks, we were able to destroy the stego content while maintaining the perceptual quality of the source image. Experimental results showed that stego content can be suppressed at least by 40%. PSNR value was found to be above 30 dB and SSIM obtained was 0.61. Markov feature and BER are used to calculate the percentage of stego removed. © Springer Nature Singapore Pte Ltd. 2017.

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2013

Journal Article

P. Premalatha and Amritha, P. P., “Optimally Locating for Hiding Information in Audio Signal”, International Journal of Computer Applications, vol. 65, no. 14, pp. 37-42, 2013.[Abstract]


Steganography provides security and privacy of information on open environment systems. Audio steganography plays a vital role in hiding information by exploiting the human ear perceptibility. In this paper, the harmonic component that are imperceptible to the human auditory system are manipulated using Fast Fourier Transform to hide data within the samples. The decoder samples the modified song and extracts the hidden message with the key, using an error correcting code to fix any bits altered by the channel. More »»

2010

Journal Article

P. P. Amritha, Madathil, A., and Dr. Gireesh K. T., “Unconditional Steganalysis of JPEG and BMP Images and Its Performance Analysis Using Support Vector Machine”, Communications in Computer and Information Science, vol. 101, pp. 638-640, 2010.[Abstract]


A feature based steganalytic method used for detecting both transform and spatial domain embedding techniques was developed. We developed an unconditional steganalysis which will automatically classify an image as having hidden information or not using a powerful classifier Support Vector Machine which is independent of any embedding techniques. To select the most relevant features from the total 269 features extracted, they apply Principal Component Analysis. Experimental results showed that our steganalysis scheme blindly detect the images obtained from six steganographic algorithms- F5, Outguess, S-Tool, JP Hide & Seek, LSB flipping and PVD. This method is able to detect any new algorithms which are not used during the training step, even if the embedding rate is very low. We also analyzed embedding rate versus detectability performances. © Springer-Verlag Berlin Heidelberg 2010.

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2010

Journal Article

A. P. Sherly and Amritha, P. P., “A compressed video steganography using TPVD”, International Journal of Database Management Systems (IJDMS) Vol, vol. 2, pp. 764–766, 2010.[Abstract]


Steganography is the art of hiding information in ways that avert the revealing of hiding messages. This paper proposes a new Compressed Video Steganographic scheme. In this algorithm, data hiding operations are executed entirely in the compressed domain. Here data are embedded in the macro blocks of I frame with maximum scene change and in block of P and B frames with maximum magnitude of motion vectors. To enlarge the capacity of the hidden secret information and to provide an imperceptible stego-image for human vision, a novel steganographic approach called tri-way pixel-value differencing (TPVD) is used for embedding. In this scheme all the processes are defined and executed in the compressed domain. Though decompression is not required. Experimental results demonstrate that the proposed algorithm has high imperceptibility and capacity. More »»

2010

Journal Article

P. P. Amritha and Dr. Gireesh K. T., “A Survey on Digital Image Steganographic Methods”, Cyber Security, Cyber Crime and Cyber Forensics: Applications and Perspectives: Applications and Perspectives, p. 250, 2010.[Abstract]


Steganography is the art of hiding information in ways that prevent the detection of hidden message, where as cryptographic techniques try to conceal the contents of a message. In steganography, the object of communication is the hidden message while the cover data is only the means of sending it. The secret information as well as the cover data can be any medium like text, image, audio, video etc. The objective of this chapter is to report various steganographic embedding schemes that can provide provable security. More »»

2010

Journal Article

P. P. Amritha and Madathil, A., “Payload Estimation in Universal Steganalysis”, Defence Science Journal, vol. 60, p. 412, 2010.[Abstract]


Universal Steganalysis can classify images without the knowledge of steganographic algorithms. This steganalysis will blindly classify an image as cover or not, but finding how much payload embedded, is still an open problem. This paper focuses on the above problem. Firstly, they use features from universal steganlysers and apply principal component analysis to improve the false positive rate. The above features are then used to estimate the payload by using support vector regression. The support vector machine classifier capable of assigning stego images to six popular steganographic algorithm after applying Principal Component Analysis: JP Hide & Seek, PVD, LSB flipping, Outguess, S-Tool and F5 is trained. This provides significantly more reliable results compared to their previous work on universal steganalysis. The performance is also evaluated by quantitative steganalysis for six steganographic algorithms. More »»

Publication Type: Book Chapter

Year of Publication Publication Type Title

2016

Book Chapter

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 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 »»

2016

Book Chapter

S. Priya and Amritha, P. P., “Information Hiding in H.264, H.265, and MJPEG”, in Proceedings of the International Conference on Soft Computing Systems: ICSCS 2015, Volume 2, P. L. Suresh and Panigrahi, K. Bijaya New Delhi: Springer India, 2016, pp. 479–487.[Abstract]


Steganography refers to the process of inserting information into a medium to secure the communication. Video steganography, which is the focus of this paper, can be viewed as an extension of image steganography. In fact, a video stream consists of a series of consecutive and equally time-spaced still images, sometimes accompanied with audio. There are many image steganographic techniques that are applicable to videos as well. In this paper, data hiding is done in H.264, H.265, and MJPEG using LSB- and PVD- based steganographic algorithms. A comparative study is also done for the above mentioned video codecs. Here, we address the issues of the least detectable steganographic algorithm when performing steganalysis in terms of MMD and the best channel and location for embedding the secret information. We also discuss the applications that work on these compression formats that can take advantage of this work. More »»

2016

Book Chapter

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 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 »»

2015

Book Chapter

A. Rahman and Amritha, P. P., “Using Signature for Hidden Communication Prevention in IP Telephony”, in Artificial Intelligence and Evolutionary Algorithms in Engineering Systems: Proceedings of ICAEES 2014, Volume 2, P. L. Suresh, Dash, S. Subhransu, and Panigrahi, K. Bijaya New Delhi: Springer India, 2015, pp. 489–494.[Abstract]


This paper prevents the steganographic method for IP telephony called transcoding steganography (TranSteg). Typically, in TranSteg, it is the overt data that is to compress to make space for steganogram. TranSteg finds appropriate codec that will result in the voice quality similar to the original. In signature-based system, the signature of the voice payload is appended to the packet to provide integrity. The signature of the data becomes invalid when there is some change in voice data. This method detects the hidden communication between a VoIP call. The signature-based scheme concept is described in this paper. More »»

2015

Book Chapter

N. Jayasree and Amritha, P. P., “A Model for the Effective Steganalysis of VoIP”, in Artificial Intelligence and Evolutionary Algorithms in Engineering Systems: Proceedings of ICAEES 2014, Volume 2, P. L. Suresh, Dash, S. Subhransu, and Panigrahi, K. Bijaya New Delhi: Springer India, 2015, pp. 379–387.[Abstract]


The latest studies and applications in steganography are based on Internet, particularly voice over IP (VoIP). VoIP has proved itself to be a perfect carrier for hidden data. Most of the approaches for VoIP steganalysis focus on detecting hidden data in the payload of the packets, by extending audio steganalysis methods. Here, we propose an effective steganalysis method which considers the speech behavior as well as network protocol structure to detect hidden communication. The common statistical features, like mean, covariance, etc., are also considered for effective classification. More »»

2015

Book Chapter

S. Anjana and Amritha, P. P., “A Novel Method for Secure Image Steganography”, in Artificial Intelligence and Evolutionary Algorithms in Engineering Systems: Proceedings of ICAEES 2014, Volume 1, P. L. Suresh, Dash, S. Subhransu, and Panigrahi, K. Bijaya New Delhi: Springer India, 2015, pp. 151–158.[Abstract]


Steganography is the science that involves communicating secret data in an appropriate multimedia carrier. The secret message is hidden in such a way that no significant degradation can be detected in the quality of the original image. In this paper, a new technique for embedding messages inside images is proposed. The pixels for message embedding are chosen such that the distortion introduced after embedding will be minimum. A distortion function is designed to calculate the cost of embedding for each pixel. The function evaluates the cost of changing an image element from directional residuals obtained using a wavelet filter bank. The intuition is to limit the embedding changes only to those parts of the cover that are difficult to model in multiple directions, avoiding smooth regions and clean edges. A technique that introduces less distortion to the carrier image will generally cause changes that are more difficult to detect, therefore providing more security. More »»

2011

Book Chapter

P. P. Amritha and Dr. Gireesh K. T., “A Survey on Digital Image Steganographic Methods”, in Cyber Security, Cyber Crime and Cyber Forensics: Applications and Perspectives, 2011, pp. 250-258.[Abstract]


The embedding schemes utilizes the characteristic of the human vision’s sensitivity to color value variations and resistant to all known steganalysis methods. The main requirement of steganography is undetectability, which loosely defines that no algorithm exists that can determine whether a work contains a hidden message. More »»

2010

Book Chapter

A. P. Sherly, Sasidharan, S., Raj, A. S., and Amritha, P. P., “A Novel Approach for Compressed Video Steganography”, in Recent Trends in Network Security and Applications: Third International Conference, CNSA 2010, Chennai, India, July 23-25, 2010. Proceedings, N. Meghanathan, Boumerdassi, S., Chaki, N., and Nagamalai, D. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 567–575.[Abstract]


Steganography is the art of hiding information in ways that avert the revealing of hiding messages. This paper proposes a new Compressed Video Steganographic scheme. In this algorithm, data hiding operations are executed entirely in the compressed domain. Here data are embedded in the macro blocks of I frame with maximum scene change. To enlarge the capacity of the hidden secret information and to provide an imperceptible stego-image for human vision, a novel steganographic approach called tri-way pixel-value differencing (TPVD) is used for embedding. In this scheme all the processes are defined and executed in the compressed domain. Though decompression is not required. Experimental results demonstrate that the proposed algorithm has high imperceptibility and capacity. More »»

Publication Type: Conference Paper

Year of Publication Publication Type Title

2014

Conference Paper

V. A. C and Amritha, P. P., “Multi-Level Steganography for Smart phones”, in Networks Soft Computing (ICNSC), 2014 First International Conference on, 2014.[Abstract]


A new approach for securing data while transmitting or storing in Smart phones has been proposed in this Research paper. The proposed method employs Multi-Level Steganography with Defense in Depth mechanism for enhanced protection of embedded data and a compression method to effectively compress the data. Multi-Level Steganography have many levels of steganography employed one after the other. It makes sure that without knowing the number of level and the methods used in each level it becomes practically impossible to detect the message. In-painting method is used for compressing secret images and YASS steganography which works on JPEG cover images is used which resists blind steganalysis on both the levels. To enhance the security in inner level One Time padding (XOR) is used. More »»

Publication Type: Conference Proceedings

Year of Publication Publication Type Title

2012

Conference Proceedings

A. Nandakumar, Amritha, P. P., Dr. Lakshmy K. V., and Talluri, V. S., “Non linear secret sharing for gray scale images”, Procedia Engineering, vol. 30. Coimbatore, pp. 945-952, 2012.[Abstract]


Most of the image secret sharing schemes employ linear secret sharing such as Shamir's secret sharing scheme. Linear secret sharing threshold schemes are vulnerable to cheating problem (Tompa-Woll attack), where a participant can submit a false share and only he will be able to obtain the correct secret. Every Linear (k,n) threshold schemes are equivalent to some Maximum distance separable (MDS) codes. Finding more MDS linear codes is difficult and therefore finding more linear threshold schemes is not easy. In 1996, A.Renvall and C. Ding proposed a non-linear secret sharing scheme based on quadratic forms. In 2001 Pieprzyk and Zhang proposed a non linear scheme based on highly non linear balanced Boolean function. Even though work on nonlinear secret sharing schemes has been done on numbers, no significant work on images has been done so far. In this paper, concept of non-linear secret sharing scheme is extended to gray scale images. Experimental results concluded that non linear secret sharing can be applied for secret image sharing. It resists the Tompa-Woll attack and also able to retrieve the correct secret image, even if some of the shares are modified by a cheater.

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