82 research outputs found
Detecting covert communication channels in raster images
Digital image steganography is a method for hiding secret messages within everyday Internet communication channels. Such covert communications provide protection for communications and exploit the opportunities available in digital media. Digital image steganography makes the nature and content of a message invisible to other users by taking ordinary internet artefacts and using them as cover objects for the messages. In this paper we demonstrate the capability with raster image files and discuss the challenges of detecting such covert communications. The contribution of the research is community awareness of covert communication capability in digital media and the motivation for including such checks in any investigatory analysis
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
Perfectly Secure Steganography Using Minimum Entropy Coupling
Steganography is the practice of encoding secret information into innocuous
content in such a manner that an adversarial third party would not realize that
there is hidden meaning. While this problem has classically been studied in
security literature, recent advances in generative models have led to a shared
interest among security and machine learning researchers in developing scalable
steganography techniques. In this work, we show that a steganography procedure
is perfectly secure under Cachin (1998)'s information-theoretic model of
steganography if and only if it is induced by a coupling. Furthermore, we show
that, among perfectly secure procedures, a procedure maximizes information
throughput if and only if it is induced by a minimum entropy coupling. These
insights yield what are, to the best of our knowledge, the first steganography
algorithms to achieve perfect security guarantees for arbitrary covertext
distributions. To provide empirical validation, we compare a minimum entropy
coupling-based approach to three modern baselines -- arithmetic coding, Meteor,
and adaptive dynamic grouping -- using GPT-2, WaveRNN, and Image Transformer as
communication channels. We find that the minimum entropy coupling-based
approach achieves superior encoding efficiency, despite its stronger security
constraints. In aggregate, these results suggest that it may be natural to view
information-theoretic steganography through the lens of minimum entropy
coupling
Information Forensics and Security: A quarter-century-long journey
Information forensics and security (IFS) is an active R&D area whose goal is to ensure that people use devices, data, and intellectual properties for authorized purposes and to facilitate the gathering of solid evidence to hold perpetrators accountable. For over a quarter century, since the 1990s, the IFS research area has grown tremendously to address the societal needs of the digital information era. The IEEE Signal Processing Society (SPS) has emerged as an important hub and leader in this area, and this article celebrates some landmark technical contributions. In particular, we highlight the major technological advances by the research community in some selected focus areas in the field during the past 25 years and present future trends
Information Analysis for Steganography and Steganalysis in 3D Polygonal Meshes
Information hiding, which embeds a watermark/message over a cover signal, has recently found extensive applications in, for example, copyright protection, content authentication and covert communication. It has been widely considered as an appealing technology to complement conventional cryptographic processes in the field of multimedia security by embedding information into the signal being protected. Generally, information hiding can be classified into two categories: steganography and watermarking. While steganography attempts to embed as much information as possible into a cover signal, watermarking tries to emphasize the robustness of the embedded information at the expense of embedding capacity.
In contrast to information hiding, steganalysis aims at detecting whether a given medium has hidden message in it, and, if possible, recover that hidden message. It can be used to measure the security performance of information hiding techniques, meaning a steganalysis resistant steganographic/watermarking method should be imperceptible not only to Human Vision Systems (HVS), but also to intelligent analysis.
As yet, 3D information hiding and steganalysis has received relatively less attention compared to image information hiding, despite the proliferation of 3D computer graphics models which are fairly promising information carriers. This thesis focuses on this relatively neglected research area and has the following primary objectives: 1) to investigate the trade-off between embedding capacity and distortion by considering the correlation between spatial and normal/curvature noise in triangle meshes; 2) to design satisfactory 3D steganographic algorithms, taking into account this trade-off; 3) to design robust 3D watermarking algorithms; 4) to propose a steganalysis framework for detecting the existence of the hidden information in 3D models and introduce a universal 3D steganalytic method under this framework. %and demonstrate the performance of the proposed steganalysis by testing it against six well-known 3D steganographic/watermarking methods.
The thesis is organized as follows. Chapter 1 describes in detail the background relating to information hiding and steganalysis, as well as the research problems this thesis will be studying. Chapter 2 conducts a survey on the previous information hiding techniques for digital images, 3D models and other medium and also on image steganalysis algorithms.
Motivated by the observation that the knowledge of the spatial accuracy of the mesh vertices does not easily translate into information related to the accuracy of other visually important mesh attributes such as normals, Chapters 3 and 4 investigate the impact of modifying vertex coordinates of 3D triangle models on the mesh normals. Chapter 3 presents the results of an empirical investigation, whereas Chapter 4 presents the results of a theoretical study. Based on these results, a high-capacity 3D steganographic algorithm capable of controlling embedding distortion is also presented in Chapter 4.
In addition to normal information, several mesh interrogation, processing and rendering algorithms make direct or indirect use of curvature information. Motivated by this, Chapter 5 studies the relation between Discrete Gaussian Curvature (DGC) degradation and vertex coordinate modifications.
Chapter 6 proposes a robust watermarking algorithm for 3D polygonal models, based on modifying the histogram of the distances from the model vertices to a point in 3D space. That point is determined by applying Principal Component Analysis (PCA) to the cover model. The use of PCA makes the watermarking method robust against common 3D operations, such as rotation, translation and vertex reordering. In addition, Chapter 6 develops a 3D specific steganalytic algorithm to detect the existence of the hidden messages embedded by one well-known watermarking method. By contrast, the focus of Chapter 7 will be on developing a 3D watermarking algorithm that is resistant to mesh editing or deformation attacks that change the global shape of the mesh.
By adopting a framework which has been successfully developed for image steganalysis, Chapter 8 designs a 3D steganalysis method to detect the existence of messages hidden in 3D models with existing steganographic and watermarking algorithms. The efficiency of this steganalytic algorithm has been evaluated on five state-of-the-art 3D watermarking/steganographic methods. Moreover, being a universal steganalytic algorithm can be used as a benchmark for measuring the anti-steganalysis performance of other existing and most importantly future watermarking/steganographic algorithms.
Chapter 9 concludes this thesis and also suggests some potential directions for future work
Semantic-Preserving Linguistic Steganography by Pivot Translation and Semantic-Aware Bins Coding
Linguistic steganography (LS) aims to embed secret information into a highly
encoded text for covert communication. It can be roughly divided to two main
categories, i.e., modification based LS (MLS) and generation based LS (GLS).
Unlike MLS that hides secret data by slightly modifying a given text without
impairing the meaning of the text, GLS uses a trained language model to
directly generate a text carrying secret data. A common disadvantage for MLS
methods is that the embedding payload is very low, whose return is well
preserving the semantic quality of the text. In contrast, GLS allows the data
hider to embed a high payload, which has to pay the high price of
uncontrollable semantics. In this paper, we propose a novel LS method to modify
a given text by pivoting it between two different languages and embed secret
data by applying a GLS-like information encoding strategy. Our purpose is to
alter the expression of the given text, enabling a high payload to be embedded
while keeping the semantic information unchanged. Experimental results have
shown that the proposed work not only achieves a high embedding payload, but
also shows superior performance in maintaining the semantic consistency and
resisting linguistic steganalysis
- …