Robust Steganographic Method with Code-Controlled Information Embedding

In view of the fact that most images are compressed when transmitted through telecommunica-tion systems and telecommunication systems in the energetics, from the point of view of the practical use of steganographic algorithms in real information security systems, such as their property, the ability to effectively resist a compression attack, is of great interest. This work aims at increasing the robustness of steganographic system against compression attacks to ensure the reliability of the steganographic message perception by developing a steganographic method that implements the embedding of additional information in the spatial domain of the container, us-ing the code control of the frequency components that are under perturbations resulting from the steganographic transformation. The goal was achieved using the code control of information embedding: due to preliminary additional coding of the embedded information with codewords for which the Walsh-Hadamard transformants have the specified properties, which leads to a given localization of disturbances in the Walsh-Hadamard domain of the container as a result of the information embedding. The most significant result is the steganographic method developed based on the formed theoretical basis, for which classes of codewords that provide the highest robustness against the compression attacks were constructed. The significance of the results ob-tained is that the developed method ensured a high reliability level of perception the ste-ganographic messages, significant robustness against the compression attacks, as well as sim-plicity of algorithmic implementation and high performance.

Multi-user transmission for the joint radar communication systems based on amplitude phase shift keying modulation and waveform diversity

In this paper, an efficient dual function radar-communication system is proposed to improve the system's resource utilization. In this work, we considered a scenario where the location of the communication receiver is known prior but the radar target is moving and its location is changing with time. Therefore, we proposed a closed-loop design that allows an adaptive selection of appropriate information embedding strategies during tracking operations. We used two strategies that utilize the amplitudes and/or phases of the transmitted radar waveforms toward the communication direction according to the position of the communication receiver during each scan. Hence, during each radar illumination, the system carries out a target-tracking task and simultaneously maintains the communication symbols transmission toward the intended communication direction. The simulation results verify the effective performance of the proposed approach in terms of target detection and tracking performance and angular bit error rate (BER). Furthermore, the proposed amplitude phase-shift keying signaling strategy can transmit different communication symbols to different users located within the sidelobe region and also provides a significant improvement in data rate transmission and BER performance compared with the existing sidelobe-based communication strategies.

Multiplex network embedding for implicit sentiment analysis

As one of the hot research directions in natural language processing, sentiment analysis has received continuous and extensive attention. Different from explicit sentiment words indicating sentiment polarity, implicit sentiment analysis is a more challenging problem due to the lack of sentiment words, which makes it inadequate to use traditional sentiment analysis method to judge the polarity of implicit sentiment. This paper takes sentiment analysis as a special sign link prediction problem, which is different from traditional text-based method. In particular, by performing the word graph-based text level information embedding and heterogeneous social network information embedding (i.e. user social relationship network embedding, and user-entity sentiment network embedding), the proposed scheme learns the highly nonlinear representations of network nodes, explores early fusion method to combine the strength of these two types of embedding modeling, optimizes all parameters simultaneously and creates enhanced context representations, leading to better capture of implicit sentiment polarity. The proposed method has been examined on real-world dataset, for implicit sentiment link prediction task. The experimental results demonstrate that the proposed method outperforms state-of-the-art schemes, including LINE, node2vec, and SDNE, by 20.2%, 19.8%, and 14.0%, respectively, on accuracy, and achieves at least 14% gains on AUROC. For sentiment analysis accuracy, the proposed method achieves AUROC of 80.6% and accuracy of 78.3%, which is at least 31% better than other models. This work can provide useful guidance on the implicit sentiment analysis.

Lossless Watermarking Algorithm Based on Multiple-Base Notational System and Pixel Difference

In order to identify the authenticity of the industrial packaging, the solution to the current watermark technology is mainly to embed the same watermark capacity into each pixel value in the image, so that the watermark capacity is small, and the anti-distortion performance is not good. Data watermarking algorithm based on system and pixel difference. First divide the carrier image into non-overlapping sub-blocks, and calculate the pixel difference of each sub-block; introduce a hybrid system to obtain different bases. According to the pixel difference, the base selection rule is defined; considering the human visual characteristics, the pixel interval adaptive adjustment mechanism is designed to improve the coding technology and complete the watermark information embedding; finally, the watermark information extraction mechanism is established to restore the watermark. The experimental results show that compared with the current data watermarking algorithm, the proposed algorithm has ideal imperceptibility, as well as larger watermark capacity and lower distortion.

Histogram based QR Code Authentication using Medical Images

Medical images require proper attention during the information embedding since the information which is to be embedded should not disturb the image quality. The remedy for the distortion caused by embedding data into medical images can be overcome by using lossless data hiding techniques. QR Code are consisting of relevant medical information that can be retrieved easily. In the present, information security become vital asset at the communication services, thereby concealing of information become a dilemma. For this issue, we employ a method known as Steganography in which the data is concealed in a medium like text, image etc., and appears to be normal, without affecting the quality of the hidden medium. Watermarking enables the protection of data format which is embedded with other data format and provides ownership access to the end user in unrecognizable format. Both steganography and watermarking techniques employ greater security to the information which can be embedded within a data format of any type.

Achieving Lightweight Privacy-Preserving Image Sharing and Illegal Distributor Detection in Social IoT

The applications of social Internet of Things (SIoT) with large numbers of intelligent devices provide a novel way for social behaviors. Intelligent devices share images according to the groups of their specified owners. However, sharing images may cause privacy disclosure when the images are illegally distributed without owners’ permission. To tackle this issue, combining blind watermark with additive secret sharing technique, we propose a lightweight and privacy-preserving image sharing (LPIS) scheme with illegal distributor detection in SIoT. Specifically, the query user’s authentication information is embedded in two shares of the transformed encrypted image by using discrete cosine transform (DCT) and additive secret sharing technique. The robustness against attacks, such as JPEG attack and the least significant bit planes (LSBs) replacement attacks, are improved by modifying 1/8 of coefficients of the transformed image. Moreover, we adopt two edge servers to provide image storage and authentication information embedding services for reducing the operational burden of clients. As a result, the identity of the illegal distributor can be confirmed by the watermark extraction of the suspicious image. Finally, we conduct security analysis and ample experiments. The results show that LPIS is secure and robust to prevent illegal distributors from modifying images and manipulating the embedded information before unlawful sharing.