Hiding Inside HTML and Other Source Codes

Many steganographic techniques were proposed for hiding secret message inside images, the simplest of them being the LSB data hiding. In this paper, we suggest a novel data hiding technique in an HTML Web page and also propose some simple techniques to extend the embedding technique to source codes written in any programming language (both case insensitive like HTML, Pascal and case sensitive languages like C, C++, Java). We basically try to exploit the case-redundancy in case-insensitive language, while we try hiding data with minimal changes in the source code (almost not raising suspicion). HTML Tags are case insensitive and hence an alphabet in lowercase and one in uppercase present inside an HTML tag are interpreted in the same manner by the browser, i.e., change in case in a web page is imperceptible to the browser. We first exploit this redundancy and use it to embed secret data inside an web page, with no changes visible to the user of the web page, so that he can not even suspect about the data hiding. The embedded data can be recovered by viewing the source of the HTML page. This technique can easily be extended to embed secret message inside any piece of source-code where the standard interpreter of that language is case-insensitive. For case-sensitive programming languages we do minimal changes in the source code (e.g., add an extra character in the token identified by the lexical analyzer) without violating the lexical and syntactic notation for that language) and try to make the change almost imperceptible.Comment: 10 Pages, 7 Figures, 2 Algorithm

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography

Data hiding is the process of embedding information into a noise-tolerant signal such as a piece of audio, video, or image. Digital watermarking is a form of data hiding where identifying data is robustly embedded so that it can resist tampering and be used to identify the original owners of the media. Steganography, another form of data hiding, embeds data for the purpose of secure and secret communication. This survey summarises recent developments in deep learning techniques for data hiding for the purposes of watermarking and steganography, categorising them based on model architectures and noise injection methods. The objective functions, evaluation metrics, and datasets used for training these data hiding models are comprehensively summarised. Finally, we propose and discuss possible future directions for research into deep data hiding techniques

The Art of Data Hiding with Reed-Solomon Error Correcting Codes

With the tremendous advancements in technology and the Internet, data security has become a major issue around the globe. To guarantee that data is protected and does not go to an unintended endpoint, the art of data hiding (steganography) emerged. Steganography is the art of hiding information such that it is not detectable to the naked eye. Various techniques have been proposed for hiding a secret message in a carrier document. In this paper, we present a novel design that applies Reed-Solomon (RS) error correcting codes in steganographic applications. The model works by substituting the redundant RS codes with the steganographic message. The experimental results show that the proposed design is satisfactory with the percentage of decoded information 100% and percentage of decoded secret message 97. 36%. The proposed model proved that it could be applied in various steganographic applications

Trends toward real-time network data steganography

Network steganography has been a well-known covert data channeling method for over three decades. The basic set of techniques and implementation tools have not changed significantly since their introduction in the early 1980's. In this paper, we review the predominant methods of classical network steganography, describing the detailed operations and resultant challenges involved in embedding data in the network transport domain. We also consider the various cyber threat vectors of network steganography and point out the major differences between classical network steganography and the widely known end-point multimedia embedding techniques, which focus exclusively on static data modification for data hiding. We then challenge the security community by introducing an entirely new network dat hiding methodology, which we refer to as real-time network data steganography. Finally we provide the groundwork for this fundamental change of covert network data embedding by forming a basic framework for real-time network data operations that will open the path for even further advances in computer network security.Comment: 20 pages introducing the concept of real-time network steganograph

On the usefulness of information hiding techniques for wireless sensor networks security

A wireless sensor network (WSN) typically consists of base stations and a large number of wireless sensors. The sensory data gathered from the whole network at a certain time snapshot can be visualized as an image. As a result, information hiding techniques can be applied to this "sensory data image". Steganography refers to the technology of hiding data into digital media without drawing any suspicion, while steganalysis is the art of detecting the presence of steganography. This article provides a brief review of steganography and steganalysis applications for wireless sensor networks (WSNs). Then we show that the steganographic techniques are both related to sensed data authentication in wireless sensor networks, and when considering the attacker point of view, which has not yet been investigated in the literature. Our simulation results show that the sink level is unable to detect an attack carried out by the nsF5 algorithm on sensed data

On Using Linear Diophantine Equations to Tune the extent of Look Ahead while Hiding Decision Tree Rules

This paper focuses on preserving the privacy of sensitive pat-terns when inducing decision trees. We adopt a record aug-mentation approach for hiding sensitive classification rules in binary datasets. Such a hiding methodology is preferred over other heuristic solutions like output perturbation or crypto-graphic techniques - which restrict the usability of the data - since the raw data itself is readily available for public use. In this paper, we propose a look ahead approach using linear Diophantine equations in order to add the appropriate number of instances while minimally disturbing the initial entropy of the nodes.Comment: 10 pages, 5 figures. arXiv admin note: substantial text overlap with arXiv:1706.0573

Securing SQLJ Source Codes from Business Logic Disclosure by Data Hiding Obfuscation

Information security is protecting information from unauthorized access, use, disclosure, disruption, modification, perusal and destruction. CAIN model suggest maintaining the Confidentiality, Authenticity, Integrity and Non-repudiation (CAIN) of information. Oracle 8i, 9i and 11g Databases support SQLJ framework allowing embedding of SQL statements in Java Programs and providing programmer friendly means to access the Oracle database. As cloud computing technology is becoming popular, SQLJ is considered as a flexible and user friendly language for developing distributed applications in grid architectures. SQLJ source codes are translated to java byte codes and decompilation is generation of source codes from intermediate byte codes. The intermediate SQLJ application byte codes are open to decompilation, allowing a malicious reader to forcefully decompile it for understanding confidential business logic or data from the codes. To the best of our knowledge, strong and cost effective techniques exist for Oracle Database security, but still data security techniques are lacking for client side applications, giving possibility for revelation of confidential business data. Data obfuscation is hiding the data in codes and we suggest enhancing the data security in SQLJ source codes by data hiding, to mitigate disclosure of confidential business data, especially integers in distributed applications.Comment: 4 pages,3 Figure

Data Hiding Techniques In Digital Images

With literally millions of images moving on the Internet each year it is safe to say that hiding data in digital image is of real concern to many in the security field. Therefore how to protect secret messages during transmission becomes an important issue. Hiding data provides a good layer of protection on the secret message, so the purpose of this thesis is to study the data hiding techniques in digital images as a new and powerful technology capable of solving important practical problems. Depending on what information in which form is hidden in the digital images, one can distinguish two types of data hiding techniques, spatial domain techniques, and frequency domain techniques. In the spatial domain techniques, a digital image serves as a carrier for a secret message. For instance, by replacing the least significant bit of each pixel in the carrier image with the secret message after changing it to stream of bits, the changes to the carrier image will be imperceptible and the secret message will be masked by carrier image. In this side, two programs had been implemented using MATLAB program to illustrate the main idea involved in least significant technique (low bit encoding), and the other to illustrate the masking technique inside the carrier image. In the frequency domain techniques, a short message is embedded in the carrier image in a robust algorithm. Robustness means the ability to survive common image processing operations, such as lossy compression, filtering, noise adding, geometrical transformations, etc. So in this technique two programs had been implemented to illustrate the main idea involved in frequency domain, one with the Fast Fourier Transform (FFT), and the other with the Discrete Wavelet Transform (DWT). After all these studies, one of the algorithms in the masking technique is developed and implemented using JAVA program to embed message into true color image with a good quality and higher capacity. Beside that the carrier images in different techniques were examined by exposing them to common signal processing operations such as image resizing, rotation, histogram equalization, lossy Compression, and Gaussian noise addition to illustrate the characteristic of the data hiding techniques, such as hiding capacity, robustness, undetectability, and perceptual transparency Finally, it has been shown that the frequency transformation techniques are more robust, and hence suitable for water marking and data hiding purpose. The spatial domain techniques exhibit loss robustness but due to its higher capacity and good quality are perfect for data hiding purposes

Data set operations to hide decision tree rules

This paper focuses on preserving the privacy of sensitive patterns when inducing decision trees. We adopt a record augmentation approach for hiding sensitive classification rules in binary datasets. Such a hiding methodology is preferred over other heuristic solutions like output perturbation or cryptographic techniques - which restrict the usability of the data - since the raw data itself is readily available for public use. We show some key lemmas which are related to the hiding process and we also demonstrate the methodology with an example and an indicative experiment using a prototype hiding tool.Comment: 7 pages, 4 figures and 2 tables. ECAI 201

Comparative Analysis of Image Stenography Techniques for Image Quality & Security

In this paper, discuss about the data hiding using the wavelet approach is better technique in stegnography techniques. optimization techniques are better results provides for the data hiding in stenography. In Discrete Wavelet Transform, HAAR Wavelet gives the excellent peak signal to noise ratio (PSNR) and less computation time. In optimization, particle swarm optimization technique is gives excellent better result in case of PSNR ratio.In spatial domain, common useful technique is least significant bit(LSB) gives better result in case of data payload capacity and less computation time. In paper mentioned, all above techniques with compare to other related techniques useful in stegnography