"The Good, The Bad And The Ugly": Evaluation of Wi-Fi Steganography

In this paper we propose a new method for the evaluation of network steganography algorithms based on the new concept of "the moving observer". We considered three levels of undetectability named: "good", "bad", and "ugly". To illustrate this method we chose Wi-Fi steganography as a solid family of information hiding protocols. We present the state of the art in this area covering well-known hiding techniques for 802.11 networks. "The moving observer" approach could help not only in the evaluation of steganographic algorithms, but also might be a starting point for a new detection system of network steganography. The concept of a new detection system, called MoveSteg, is explained in detail.Comment: 6 pages, 6 figures, to appear in Proc. of: ICNIT 2015 - 6th International Conference on Networking and Information Technology, Tokyo, Japan, November 5-6, 201

Hidden and Uncontrolled - On the Emergence of Network Steganographic Threats

Network steganography is the art of hiding secret information within innocent network transmissions. Recent findings indicate that novel malware is increasingly using network steganography. Similarly, other malicious activities can profit from network steganography, such as data leakage or the exchange of pedophile data. This paper provides an introduction to network steganography and highlights its potential application for harmful purposes. We discuss the issues related to countering network steganography in practice and provide an outlook on further research directions and problems.Comment: 11 page

Micro protocol engineering for unstructured carriers: On the embedding of steganographic control protocols into audio transmissions

Network steganography conceals the transfer of sensitive information within unobtrusive data in computer networks. So-called micro protocols are communication protocols placed within the payload of a network steganographic transfer. They enrich this transfer with features such as reliability, dynamic overlay routing, or performance optimization --- just to mention a few. We present different design approaches for the embedding of hidden channels with micro protocols in digitized audio signals under consideration of different requirements. On the basis of experimental results, our design approaches are compared, and introduced into a protocol engineering approach for micro protocols.Comment: 20 pages, 7 figures, 4 table

Steganographic Generative Adversarial Networks

Steganography is collection of methods to hide secret information ("payload") within non-secret information "container"). Its counterpart, Steganalysis, is the practice of determining if a message contains a hidden payload, and recovering it if possible. Presence of hidden payloads is typically detected by a binary classifier. In the present study, we propose a new model for generating image-like containers based on Deep Convolutional Generative Adversarial Networks (DCGAN). This approach allows to generate more setganalysis-secure message embedding using standard steganography algorithms. Experiment results demonstrate that the new model successfully deceives the steganography analyzer, and for this reason, can be used in steganographic applications.Comment: 15 pages, 10 figures, 5 tables, Workshop on Adversarial Training (NIPS 2016, Barcelona, Spain

Unified Description for Network Information Hiding Methods

Until now hiding methods in network steganography have been described in arbitrary ways, making them difficult to compare. For instance, some publications describe classical channel characteristics, such as robustness and bandwidth, while others describe the embedding of hidden information. We introduce the first unified description of hiding methods in network steganography. Our description method is based on a comprehensive analysis of the existing publications in the domain. When our description method is applied by the research community, future publications will be easier to categorize, compare and extend. Our method can also serve as a basis to evaluate the novelty of hiding methods proposed in the future.Comment: 24 pages, 7 figures, 1 table; currently under revie