PRUDA: A Novel Measurement Attribute Set towards Robust Steganography in Social Networks

Cloud services have become an increasingly popular solution to provide different services to clients. More and more data are outsourced to the cloud for storage and computing. With this comes concern about the security of outsourced data. In recent years, homomorphic encryption, blockchain, steganography, and other technologies have been applied to the security and forensics of outsourced data. While encryption technologies such as homomorphic encryption and blockchain scramble data so that they cannot be understood, steganography hides the data so that they cannot be observed. Traditional steganography assumes that the environment is lossless. Robust steganography is grounded in traditional steganography and is proposed based on a real lossy social network environment. Thus, researchers, who study robust steganography, believe that the measurement should follow traditional steganography. However, the application scenario of robust steganography breaks through the traditional default lossless environment premise. It brings about changes in the focus of steganography algorithms. Simultaneously, the existing steganography methods miss the evaluation of applicability and ease of use. In this paper, “default parameters” are observed by comparing the process of robust image steganography with traditional image steganography. The idea of “perfecting default parameters” is proposed. Based on this, the attribute set of measuring robust image steganography is presented. We call it PRUDA (Payload, Robustness, ease of Use, antiDetection, and Applicability). PRUDA perfects default parameters observed in the process of traditional steganography algorithms. Statistics on image processing attacks in mobile social apps and analyses on existing algorithms have verified that PRUDA is reasonable and can better measure a robust steganography method in practical application scenarios.

Robust Steganography over Noisy Channel

Steganography is accomplished by frequency or spatial domain. In spatial domain method, the important data are inserted directly into the image's pixels. Alternatively, the coefficients of the image frequency transform like DCT are used to carry the important data. Robustness in the presence of a noise is important. In this paper, the robustness over a noisy channel with noise like Added White Gaussian Noise (AWGN), salt and pepper noise and Speckle noise is investigated. The bit error rate is used for system evaluation. Simulation outcomes demonstrate that the frequency based model is stronger than spatial method against channel noise. Moreover, robustness is enhanced via using error correction.

EasyStego: Robust Steganography Based on Quick-Response Barcodes for Crossing Domains

Despite greater attention being paid to sensitive-information leakage in the cyberdomain, the sensitive-information problem of the physical domain remains neglected. Anonymous users can easily access the sensitive information of other users, such as transaction information, health status, and addresses, without any advanced technologies. Ideally, secret messages should be protected not only in the cyberdomain but also in the complex physical domain. However, popular steganography schemes only work in the traditional cyberdomain and are useless when physical distortions of messages are unavoidable. This paper first defines the concept of cross-domain steganography, and then proposes EasyStego, a novel cross-domain steganography scheme. EasyStego is based on the use of QR barcodes as carriers; therefore, it is robust to physical distortions in the complex physical domain. Moreover, EasyStego has a large capacity for embeddable secrets and strong scalability in various scenarios. EasyStego uses an AES encryption algorithm to control the permissions of secret messages, which is more effective in reducing the possibility of sensitive-information leakage. Experiments show that EasyStego has perfect robustness and good efficiency. Compared with the best current steganography scheme based on barcodes, EasyStego has greater steganographic capacity and less impact on barcode data. In robustness tests, EasyStego successfully extracts secret messages at different angles and distances. In the case of adding natural textures and importing quantitative error bits, other related steganography techniques fail, whereas EasyStego can extract secret messages with a success rate of nearly 100%.

Robust Steganography in Non-QRS Regions of 2D ECG for Securing Patients' Confidential Information in E-Healthcare Paradigm

The upsurge in the communication infrastructure and development in internet of things (IoT) has promoted e-healthcare services to provide remote assistance to homebound patients. It, however, increases the demand to protect the confidential information from intentional and unintentional access by unauthorized persons. This chapter is focused on steganography-based data hiding technique for ECG signal in which the selected ECG samples of non-QRS region are explored to embed the secret information. An embedding site selection (ESS) algorithm is designed to find the optimum embedding locations. The performance of the method is evaluated on the basis of statistical parameters and clinically supportive measures. The efficiency is measured in terms of embedding capacity and BER while key space measures its robustness. The implementation has been tested on standard MIT-BIH arrhythmia database of 2 mins and 5 mins duration and found that the proposed technique embarks the proficiency to securely hide the secret information at minimal distortion.