Application of Steganography for Anonymity through the Internet

In this paper, a novel steganographic scheme based on chaotic iterations is proposed. This research work takes place into the information hiding security framework. The applications for anonymity and privacy through the Internet are regarded too. To guarantee such an anonymity, it should be possible to set up a secret communication channel into a web page, being both secure and robust. To achieve this goal, we propose an information hiding scheme being stego-secure, which is the highest level of security in a well defined and studied category of attacks called "watermark-only attack". This category of attacks is the best context to study steganography-based anonymity through the Internet. The steganalysis of our steganographic process is also studied in order to show it security in a real test framework.Comment: 14 page

Blindspot: Indistinguishable Anonymous Communications

Communication anonymity is a key requirement for individuals under targeted surveillance. Practical anonymous communications also require indistinguishability - an adversary should be unable to distinguish between anonymised and non-anonymised traffic for a given user. We propose Blindspot, a design for high-latency anonymous communications that offers indistinguishability and unobservability under a (qualified) global active adversary. Blindspot creates anonymous routes between sender-receiver pairs by subliminally encoding messages within the pre-existing communication behaviour of users within a social network. Specifically, the organic image sharing behaviour of users. Thus channel bandwidth depends on the intensity of image sharing behaviour of users along a route. A major challenge we successfully overcome is that routing must be accomplished in the face of significant restrictions - channel bandwidth is stochastic. We show that conventional social network routing strategies do not work. To solve this problem, we propose a novel routing algorithm. We evaluate Blindspot using a real-world dataset. We find that it delivers reasonable results for applications requiring low-volume unobservable communication.Comment: 13 Page

Using Facebook for Image Steganography

Because Facebook is available on hundreds of millions of desktop and mobile computing platforms around the world and because it is available on many different kinds of platforms (from desktops and laptops running Windows, Unix, or OS X to hand held devices running iOS, Android, or Windows Phone), it would seem to be the perfect place to conduct steganography. On Facebook, information hidden in image files will be further obscured within the millions of pictures and other images posted and transmitted daily. Facebook is known to alter and compress uploaded images so they use minimum space and bandwidth when displayed on Facebook pages. The compression process generally disrupts attempts to use Facebook for image steganography. This paper explores a method to minimize the disruption so JPEG images can be used as steganography carriers on Facebook.Comment: 6 pages, 4 figures, 2 tables. Accepted to Fourth International Workshop on Cyber Crime (IWCC 2015), co-located with 10th International Conference on Availability, Reliability and Security (ARES 2015), Toulouse, France, 24-28 August 201

Recent Advances in Steganography

Steganography is the art and science of communicating which hides the existence of the communication. Steganographic technologies are an important part of the future of Internet security and privacy on open systems such as the Internet. This book's focus is on a relatively new field of study in Steganography and it takes a look at this technology by introducing the readers various concepts of Steganography and Steganalysis. The book has a brief history of steganography and it surveys steganalysis methods considering their modeling techniques. Some new steganography techniques for hiding secret data in images are presented. Furthermore, steganography in speeches is reviewed, and a new approach for hiding data in speeches is introduced

Steganalysis of YASS using Huffman Length statistics

This work proposes two main contributions to statistical steganalysis of Yet Another Steganographic Scheme (YASS) in JPEG images. Firstly, this work presents a reliable blind steganalysis technique to predict YASS which is one of recent and least statistically detectable embedding scheme using only five features, four Huffman length statistics (H) and the ratio of file size to resolution (FR Index). Secondly these features are shown to be unique, accurate and monotonic over a wide range of settings for YASS and several supervised classifiers with the accuracy of prediction superior to most blind steganalyzers in vogue. Overall, the proposed model having Huffman Length Statistics as its linchpin predicts YASS with an average accuracy of over 94 percent

Building a dataset for image steganography

Image steganography and steganalysis techniques discussed in the literature rely on using a dataset(s)created based on cover images obtained from the public domain, through the acquisition of images from Internet sources, or manually. This issue often leads to challenges in validating, benchmarking, and reproducing reported techniques in a consistent manner. It is our view that the steganography/steganalysis research community would benefit from the availability of common datasets, thus promoting transparency and academic integrity. In this research, we have considered four aspects: image acquisition, pre-processing, steganographic techniques, and embedding rate in building a dataset for image steganography

An improved randomization of a multi-blocking jpeg based steganographic system.

Thesis (M.Sc.)-University of KwaZulu-Natal, Durban, 2010.Steganography is classified as the art of hiding information. In a digital context, this refers to our ability to hide secret messages within innocent digital cover data. The digital domain offers many opportunities for possible cover mediums, such as cloud based hiding (saving secret information within the internet and its structure), image based hiding, video and audio based hiding, text based documents as well as the potential of hiding within any set of compressed data. This dissertation focuses on the image based domain and investigates currently available image based steganographic techniques. After a review of the history of the field, and a detailed survey of currently available JPEG based steganographic systems, the thesis focuses on the systems currently considered to be secure and introduces mechanisms that have been developed to detect them. The dissertation presents a newly developed system that is designed to counter act the current weakness in the YASS JPEG based steganographic system. By introducing two new levels of randomization to the embedding process, the proposed system offers security benefits over YASS. The introduction of randomization to the B‐block sizes as well as the E‐block sizes used in the embedding process aids in increasing security and the potential for new, larger E‐block sizes also aids in providing an increased set of candidate coefficients to be used for embedding. The dissertation also introduces a new embedding scheme which focuses on hiding in medium frequency coefficients. By hiding in these medium frequency coefficients, we allow for more aggressive embedding without risking more visual distortion but trade this off with a risk of higher error rates due to compression losses. Finally, the dissertation presents simulation aimed at testing the proposed system performance compared to other JPEG based steganographic systems with similar embedding properties. We show that the new system achieves an embedding capacity of 1.6, which represents round a 7 times improvement over YASS. We also show that the new system, although introducing more bits in error per B‐block, successfully allows for the embedding of up to 2 bits per B‐block more than YASS at a similar error rate per B‐block. We conclude the results by demonstrating the new systems ability to resist detection both through human observation, via a survey, as well as resist computer aided analysis