Hiding in Plain Sight: Scrubbing Unwanted Information

Steganography is a technique used to hide encrypted messages within multimedia files. This technique was recently reported to have been used by Osama Bin Laden to communicate with terrorist cells within the United States, and, thus, prevention of the transmission of steganographic content is of great interest to those interested in information security. Methods of steganalysis have been developed that attempt to detect files that contain steganographic content. However, authors of these methods admit that they are not viable for production or have been shown to be defeated by newer advances in steganography. This design science research illustrates an innovation in which algorithms neutralize any hidden messages without significantly detracting from the underlying integrity of the multimedia files and without the need for prior detection of steganographic content

Digital Steganalysis: Review on Recent Approaches

Abstract:Steganography is the art and science of secret communication, aiming to conceal the existence of a communication, which has been used in military, and perhaps terrorists. Steganography in the modern day sense of the word usually refers to information or a file that has been concealed inside a digital Picture, Video or Audio file. In steganography, the actual information is not maintained in its original format and thereby it is converted into an alternative equivalent multimedia file like image, video or audio, which in turn is being hidden within another object. Information Security is becoming an inseparable part of Data Communication. In order to address this Information Security, Steganography plays an important role. The digital media steganalysis is divided into three domains, which are image steganalysis, audio steganalysis, and video steganalysis. DNA sequences possess some interesting properties, which can be utilized to hide data. This paper is a review of the recent steganography techniques and utilization of DNA sequence appeared in the literature

A forensics software toolkit for DNA steganalysis.

Recent advances in genetic engineering have allowed the insertion of artificial DNA strands into the living cells of organisms. Several methods have been developed to insert information into a DNA sequence for the purpose of data storage, watermarking, or communication of secret messages. The ability to detect, extract, and decode messages from DNA is important for forensic data collection and for data security. We have developed a software toolkit that is able to detect the presence of a hidden message within a DNA sequence, extract that message, and then decode it. The toolkit is able to detect, extract, and decode messages that have been encoded with a variety of different coding schemes. The goal of this project is to enable our software toolkit to determine with which coding scheme a message has been encoded in DNA and then to decode it. The software package is able to decode messages that have been encoded with every variation of most of the coding schemes described in this document. The software toolkit has two different options for decoding that can be selected by the user. The first is a frequency analysis approach that is very commonly used in cryptanalysis. This approach is very fast, but is unable to decode messages shorter than 200 words accurately. The second option is using a Genetic Algorithm (GA) in combination with a Wisdom of Artificial Crowds (WoAC) technique. This approach is very time consuming, but can decode shorter messages with much higher accuracy

Steganography and steganalysis: data hiding in Vorbis audio streams

The goal of the current work is to introduce ourselves in the world of steganography and steganalysis, centering our efforts in acoustic signals, a branch of steganography and steganalysis which has received much less attention than steganography and steganalysis for images. With this purpose in mind, it’s essential to get first a basic level of understanding of signal theory and the properties of the Human Auditory System, and we will dedicate ourselves to that aim during the first part of this work. Once established those basis, in the second part, we will obtain a precise image of the state of the art in steganographic and steganalytic sciences, from which we will be able to establish or deduce some good practices guides. With both previous subjects in mind, we will be able to create, design and implement a stego-system over Vorbis audio codec and, finally, as conclusion, analyze it using the principles studied during the first and second parts

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

Reversible Data Hiding over Facebook

Facebook, the most popular Online Social Network (OSN), could be used as a platform to share secret messages through JPEG images online. However, due to the various lossy operations conducted over Facebook, the data embedded into the JPEG images can be easily destroyed, making the data extraction infeasible. More importantly, all these operations are carried out without users’ interference. In this paper, we first perform an in-depth investigation of the various lossy operations that Facebook applies to uploaded images. Based upon such prior knowledge, we propose a DCT-domain data hiding scheme that can effectively embed a large amount of data and successfully extract them out from the downloaded images, defeating the uncontrolled lossy operations. Compared with the state-of-the-art techniques, the proposed method offers much higher embedding capacity, and can extract the data successfully with very high probability. Furthermore, the restored image upon data extraction is of high quality, and the file size expansion is negligible. Extensive experimental results are provided to validate our findings

Defenses against Covert-Communications in Multimedia and Sensor Networks

Steganography and covert-communications represent a great and real threat today more than ever due to the evolution of modern communications. This doctoral work proposes defenses against such covert-communication techniques in two threatening but underdeveloped domains. Indeed, this work focuses on the novel problem of visual sensor network steganalysis but also proposes one of the first solutions against video steganography. The first part of the dissertation looks at covert-communications in videos. The contribution of this study resides in the combination of image processing using motion vector interpolation and non-traditional detection theory to obtain better results in identifying the presence of embedded messages in videos compared to what existing still-image steganalytic solutions would offer. The proposed algorithm called MoViSteg utilizes the specifics of video, as a whole and not as a series of images, to decide on the occurrence of steganography. Contrary to other solutions, MoViSteg is a video-specific algorithm, and not a repetitive still-image steganalysis, and allows for detection of embedding in partially corrupted sequences. This dissertation also lays the foundation for the novel study of visual sensor network steganalysis. We develop three different steganalytic solutions to the problem of covert-communications in visual sensor networks. Because of the inadequacy of the existing steganalytic solutions present in the current research literature, we introduce the novel concept of preventative steganalysis, which aims at discouraging potential steganographic attacks. We propose a set of solutions with active and passive warden scenarii using the material made available by the network. To quantify the efficiency of the preventative steganalysis, a new measure for evaluating the risk of steganography is proposed: the embedding potential which relies on the uncertainty of the image’s pixel values prone to corruption