A Study of Data Security on E-Governance using Steganographic Optimization Algorithms

Steganography has been used massively in numerous fields to maintain the privacy and integrity of messages transferred via the internet. The need to secure the information has augmented with the increase in e-governance usage. The wide adoption of e-governance services also opens the doors to cybercriminals for fraudulent activities in cyberspace. To deal with these cybercrimes we need optimized and advanced steganographic techniques. Various advanced optimization techniques can be applied to steganography to obtain better results for the security of information. Various optimization techniques like particle swarm optimization and genetic algorithms with cryptography can be used to protect information for e-governance services. In this study, a comprehensive review of steganographic algorithms using optimization techniques is presented. A new perspective on using this technique to protect the information for e-governance is also presented. Deep Learning might be the area that can be used to automate the steganography process in combination with other method

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

Designing Secure and Survivable Stegosystems

Steganography, the art and science of carrying out hidden communication, is an emergingsub-discipline of information security. Unlike cryptography, steganography conceals the existenceof a secret message by embedding it in an innocuous container digital media, thereby enablingunobstrusive communication over insecure channels. Detection and extraction of steganographiccontents is another challenge for the information security professional and this activity iscommonly known as steganalysis. Recent progress in steganalysis has posed a challenge fordesign and development of stegosystems with high levels of security and survivability. In thispaper, different strategies have been presented that can be used to escape detection and foilan eavesdropper having high technical capabilities as well as adequate infrastructure. Based onthe strength and weaknesses of current steganographic schemes, ideas have been progressedto make detection and destruction of hidden information more difficult

Enhanced Stegano-Cryptographic Model for Secure Electronic Voting

The issue of security in Information and Communication Technology has been identified as the most critical barrier in the widespread adoption of electronic voting (e-voting). Earlier cryptographic models for secure e-voting are vulnerable to attacks and existing stegano-cryptographic models can be manipulated by an eavesdropper. These shortcomings of existing models of secure e-voting are threats to confidentiality, integrity and verifiability of electronic ballot which are critical to overall success of e-democratic decision making through e-voting.This paper develops an enhanced stegano-cryptographic model for secure electronic voting system in poll-site, web and mobile voting scenarios for better citizens’ participation and credible e-democratic election. The electronic ballot was encrypted using Elliptic Curve Cryptography and Rivest-Sharma-Adleman cryptographic algorithm. The encrypted voter’s ballot was scattered and hidden in the Least Significant Bit (LSB) of the cover media using information hiding attribute of modified LSB-Wavelet steganographic algorithm. The image quality of the model, stego object was quantitatively assessed using Peak Signal to Noise Ratio (PSNR), Signal to Noise Ratio (SNR), Root Mean Square Error (RMSE) and Structural Similarity Index Metrics (SSIM).The results after quantitative performance evaluation shows that the developed stegano-cryptographic model has generic attribute of secured e-voting relevant for the delivery of credible e-democratic decision making. The large scale implementation of the model would be useful to deliver e-voting of high electoral integrity and political trustworthiness, where genuine e-elections are conducted for the populace by government authority. Keywords: Electronic Voting, Cryptography, Steganography, Video, Image, Wavelet, Securit

Adopt an optimal location using a genetic algorithm for audio steganography

With the development of technologies, most of the users utilizing the Internet for transmitting information from one place to another place. The transmitted data may be affected because of the intermediate user. Therefore, the steganography approach is applied for managing the secret information. Here audio steganography is utilized to maintain the secret information by hiding the image into the audio files. In this work, discrete cosine transforms, and discrete wavelet transform is applied to perform the Steganalysis process. The optimal hiding location has been identified by using the optimization technique called a genetic algorithm. The method utilizes the selection, crossover and mutation operators for selecting the best location. The chosen locations are difficult to predict by unauthorized users because the embedded location is varied from information to information. Then the efficiency of the system ensures the high PSNR, structural similarity index (SSIM), minimum mean square error value and Jaccard, which is evaluated on the audio Steganalysis dataset

Secure digital documents using Steganography and QR Code

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonWith the increasing use of the Internet several problems have arisen regarding the processing of electronic documents. These include content filtering, content retrieval/search. Moreover, document security has taken a centre stage including copyright protection, broadcast monitoring etc. There is an acute need of an effective tool which can find the identity, location and the time when the document was created so that it can be determined whether or not the contents of the document were tampered with after creation. Owing the sensitivity of the large amounts of data which is processed on a daily basis, verifying the authenticity and integrity of a document is more important now than it ever was. Unsurprisingly document authenticity verification has become the centre of attention in the world of research. Consequently, this research is concerned with creating a tool which deals with the above problem. This research proposes the use of a Quick Response Code as a message carrier for Text Key-print. The Text Key-print is a novel method which employs the basic element of the language (i.e. Characters of the alphabet) in order to achieve authenticity of electronic documents through the transformation of its physical structure into a logical structured relationship. The resultant dimensional matrix is then converted into a binary stream and encapsulated with a serial number or URL inside a Quick response Code (QR code) to form a digital fingerprint mark. For hiding a QR code, two image steganography techniques were developed based upon the spatial and the transform domains. In the spatial domain, three methods were proposed and implemented based on the least significant bit insertion technique and the use of pseudorandom number generator to scatter the message into a set of arbitrary pixels. These methods utilise the three colour channels in the images based on the RGB model based in order to embed one, two or three bits per the eight bit channel which results in three different hiding capacities. The second technique is an adaptive approach in transforming domain where a threshold value is calculated under a predefined location for embedding in order to identify the embedding strength of the embedding technique. The quality of the generated stego images was evaluated using both objective (PSNR) and Subjective (DSCQS) methods to ensure the reliability of our proposed methods. The experimental results revealed that PSNR is not a strong indicator of the perceived stego image quality, but not a bad interpreter also of the actual quality of stego images. Since the visual difference between the cover and the stego image must be absolutely imperceptible to the human visual system, it was logically convenient to ask human observers with different qualifications and experience in the field of image processing to evaluate the perceived quality of the cover and the stego image. Thus, the subjective responses were analysed using statistical measurements to describe the distribution of the scores given by the assessors. Thus, the proposed scheme presents an alternative approach to protect digital documents rather than the traditional techniques of digital signature and watermarking