Coverless image steganography using morphed face recognition based on convolutional neural network

In recent years, information security has become a prime issue of worldwide concern. To improve the validity and proficiency of the image data hiding approach, a piece of state-of-the-art secret information hiding transmission scheme based on morphed face recognition is proposed. In our proposed data hiding approach, a group of morphed face images is produced from an arranged small-scale face image dataset. Then, a morphed face image which is encoded with a secret message is sent to the receiver. The receiver uses powerful and robust deep learning models to recover the secret message by recognizing the parents of the morphed face images. Furthermore, we design two novel Convolutional Neural Network (CNN) architectures (e.g. MFR-Net V1 and MFR-Net V2) to perform morphed face recognition and achieved the highest accuracy compared with existing networks. Additionally, the experimental results show that the proposed schema has higher retrieval capacity and accuracy and it provides better robustness

A Novel Design to Minimise the Energy Consumption and Node Traversing in Blockchain Over Cloud Using Ensemble Cuckoo Model

The article outlines the Blockchain’s behavioral model for services. Their reliability is proven through the use of experimental evidence. The authors highlight the major technical aspects and characteristics that are associated with the transmission of data through the network. The authors define the scheme for the network, which works with blockchain transactions, and the relationship between network characteristics on parameters used by the application. They examine the use of this model to identification of the blockchain service and also the likelihood of existing security mechanisms that are based on the technology being bypassed. Additionally, the article provides guidelines to conceal the Blockchain's traffic profile to make it more difficult for its detection in the information network. This study offers a thorough analysis of blockchain-based trust models applied to cloud computing. The paper highlights the challenges that remain unsolved and offers suggestions for future studies in the area based on new cloud-edge trust management system and double-blockchain structure, which is a cloud-based transaction model. The paper also identifies the existing challenges and offers suggestions for future studies in the area based on new cloud-edge trust management system and double-blockchain structure, which is a cloud-based transaction model. The flow of the network will be supported by models that are enhanced by cuckoo to frame the perfect network transform of data from one point to cluster, or alternatively

DYST (Did You See That?): An Amplified Covert Channel That Points To Previously Seen Data

Covert channels are unforeseen and stealthy communication channels that enable manifold adversary scenarios. However, they can also allow the exchange of confidential information by journalists. All covert channels described until now therefore need to craft seemingly legitimate information flows for their information exchange, mimicking unsuspicious behavior. In this paper, we present DYST, which represents a new class of covert channels we call history covert channels jointly with the new paradigm of covert channel amplification. History covert channels can communicate almost exclusively by pointing to unaltered legitimate traffic created by regular network nodes. Only a negligible fraction of the covert communication process requires the transfer of actual covert channel information by the covert channel's sender. This allows, for the first time, an amplification of the covert channel's message size, i.e., minimizing the fraction of actually transferred secret data by a covert channel's sender in relation to the overall secret data being exchanged. We extend the current taxonomy for covert channels to show how history channels can be categorized. We describe multiple scenarios in which history covert channels can be realized, theoretically analyze the characteristics of these channels and show how their configuration can be optimized for different implementations. We further evaluate the robustness and detectability of history covert channels.Comment: 18 pages, rev

A Novel TRNG Based on Traditional ADC Nonlinear Effect and Chaotic Map for IoT Security and Anticollision

In the rapidly developing Internet of Things (IoT) applications, how to achieve rapid identification of massive devices and secure the communication of wireless data based on low cost and low power consumption is the key problem to be solved urgently. This paper proposes a novel true random number generator (TRNG) based on ADC nonlinear effect and chaotic map, which can be implemented by traditional processors with built-in ADCs, such as MCU, DSP, ARM, and FPGA. The processor controls the ADC to sample the changing input signal to obtain the digital signal DADC and then extracts some bits of DADC to generate the true random number (TRN). At the same time, after a delay based on DADC, the next time ADC sampling is carried out, and the cycle continues until the processor stops generating the TRN. Due to the nonlinear effect of ADC, the DADC obtained from each sampling is stochastic, and the changing input signal will sharply change the delay time, thus changing the sampling interval (called random interval sampling). As the input signal changes, DADC with strong randomness is obtained. The whole operation of the TRNG resembles a chaotic map, and this method also eliminates the pseudorandom property of chaotic map by combining the variable input signal (including noise) with the nonlinear effect of ADC. The simulation and actual test data are verified by NIST, and the verification results show that the random numbers generated by the proposed method have strong randomness and can be used to implement TRNG. The proposed TRNG has the advantages of low cost, low power consumption, and strong compatibility, and the rate of generating true random number is more than 1.6 Mbps (determined by ADC sampling rate and processor frequency), which is very suitable for IoT sensor devices for security encryption algorithms and anticollision

Data Hiding and Its Applications

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others