A study on the false positive rate of Stegdetect

In this paper we analyse Stegdetect, one of the well-known image steganalysis tools, to study its false positive rate. In doing so, we process more than 40,000 images randomly downloaded from the Internet using Google images, together with 25,000 images from the ASIRRA (Animal Species Image Recognition for Restricting Access) public corpus. The aim of this study is to help digital forensic analysts, aiming to study a large number of image files during an investigation, to better understand the capabilities and the limitations of steganalysis tools like Stegdetect. The results obtained show that the rate of false positives generated by Stegdetect depends highly on the chosen sensitivity value, and it is generally quite high. This should support the forensic expert to have better interpretation in their results, and taking the false positive rates into consideration. Additionally, we have provided a detailed statistical analysis for the obtained results to study the difference in detection between selected groups, close groups and different groups of images. This method can be applied to any steganalysis tool, which gives the analyst a better understanding of the detection results, especially when he has no prior information about the false positive rate of the tool

Text hiding in text using invisible character

Steganography can be defined as the art and science of hiding information in the data that could be read by computer. This science cannot recognize stego-cover and the original one whether by eye or by computer when seeing the statistical samples. This paper presents a new method to hide text in text characters. The systematic method uses the structure of invisible character to hide and extract secret texts. The creation of secret message comprises four main stages such using the letter from the original message, selecting the suitable cover text, dividing the cover text into blocks, hiding the secret text using the invisible character and comparing the cover-text and stego-object. This study uses an invisible character (white space) position of in the cover text that used to hide the the secrete sender masseges. The experiments results show that the suggested method presents highly secret due to use the multi-level of complexity to avoid the attackers

Undetectable Communication: The Online Social Networks Case

Online Social Networks (OSNs) provide users with an easy way to share content, communicate, and update others about their activities. They also play an increasingly fundamental role in coordinating and amplifying grassroots movements, as demonstrated by recent uprisings in, e.g., Egypt, Tunisia, and Turkey. At the same time, OSNs have become primary targets of tracking, profiling, as well as censorship and surveillance. In this paper, we explore the notion of undetectable communication in OSNs and introduce formal definitions, alongside system and adversarial models, that complement better understood notions of anonymity and confidentiality. We present a novel scheme for secure covert information sharing that, to the best of our knowledge, is the first to achieve undetectable communication in OSNs. We demonstrate, via an open-source prototype, that additional costs are tolerably low

Steganalysis of 3D objects using statistics of local feature sets

3D steganalysis aims to identify subtle invisible changes produced in graphical objects through digital watermarking or steganography. Sets of statistical representations of 3D features, extracted from both cover and stego 3D mesh objects, are used as inputs into machine learning classifiers in order to decide whether any information was hidden in the given graphical object. The features proposed in this paper include those representing the local object curvature, vertex normals, the local geometry representation in the spherical coordinate system. The effectiveness of these features is tested in various combinations with other features used for 3D steganalysis. The relevance of each feature for 3D steganalysis is assessed using the Pearson correlation coefficient. Six different 3D watermarking and steganographic methods are used for creating the stego-objects used in the evaluation study

A Secure Image Steganography using LSB, DCT and Compression Techniques on Raw Images

Steganography is an important area of research in recent years involving a number of applications. It is the science of embedding information into the cover image viz., text, video, and image (payload) without causing statistically significant modification to the cover image. The modern secure image steganography presents a challenging task of transferring the embedded information to the destination without being detected. In this paper we present an image based steganography that combines Least Significant Bit(LSB), Discrete Cosine Transform(DCT), and compression techniques on raw images to enhance the security of the payload. Initially, the LSB algorithm is used to embed the payload bits into the cover image to derive the stego-image. The stego-image is transformed from spatial domain to the frequency domain using DCT. Finally quantization and runlength coding algorithms are used for compressing the stego-image to enhance its security. It is observed that secure images with low MSE and BER are transferred without using any password, in comparison with earlier works

Multilevel Steganography to Improve Secret Communication

This chapter presents multilevel audio steganography, which describes a new model for hidden communication in secret communication technology. At least two embedding methods are used in such a way that the second method will use the first method as a carrier. The proposed method has several potential benefits in hidden communication. This method can be used to increase the level of security while transmitting the confidential information over public channels or internet and also can be used to provide two or more information hiding solutions simultaneously. The performance of the proposed method in terms of imperceptibility, capacity & security is measured through different experiments

Secure Data Transmission by using Steganography

Steganography is the efficient technique to provide secure data transmission over the network, as the number of users increases effectively. The cryptography is also used to provide security to data over network, but transmission of secured message may be detectable to third party. From security point of view, steganography does not allow to detect the presence of hidden secret other than indeed user, over the communication channel. In this paper, we design a system, which uses features of both cryptography as well as steganography, where TCP/IP header is used as a steganographic carrier to hide encrypted data. Steganography is a useful tool that allows covert transmission of information over the communications channel. Copyright © www.iiste.org Keywords: Steganography, Cryptography, Encryption, TCP/I