Confidential Data Transmission Research Articles

Advanced Privacy Scheme to Improve Road Safety in Smart Transportation Systems

In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.

A Secure Emergency Data Handling in Wireless Body Area Network Using Channel Allocation Schema

ABSTRACT: The Wireless Body Area Network is universal tool based on block chain storage as ledgers to handle patient Database confidentially and avoid loss of data in recent data handling technologies with distributed storage. This solves the major drawback of wireless nodes with high degree of security with highly confidential data transmission among the Wireless Body Area Network also called WBAN nodes. The major challenge is to handle emergency data from the patients at any time. Hence this research work aims to focus the emergency data handling with channel sensation and data fixation in ledgers based on channel allocation. [1] The simulated output shows the data transmission with low delay and high channel utilization and enhanced throughput. Key Terms: WBAN, block chain, channel utilization, emergency data

Secure and resilient improved image steganography using hybrid fuzzy neural network with fuzzy logic

The exponential growth in communication networks, data technology, advanced libraries, and mainly World Wide Web services has played a pivotal role in facilitating the retrieval of various types of information as needed. However, this progress has also led to security concerns related to the transmission of confidential data. Nevertheless, safeguarding these data during communication through insecure channels is crucial for obvious reasons. The emergence of steganography offers a robust approach to concealing confidential information, such as images, audio tracks, text files, and video files, in suitable media carriers. A novel technique is envisioned based on back-propagation learning. According to the proposed method, a hybrid fuzzy neural network (HFNN) is applied to the output obtained from the least significant bit substitution of secret data using pixel value differences and exploiting the modification direction. Through simulation and test results, it has been observed that the proposed methodology achieves secure steganography and superior visual quality. During the experiments, we observed that for the secret image of the cameraman, the PSNR & MSE values of the proposed technique are 61.963895 and 0.041361, respectively.

Method of information protection based on the integration of probabilistic encryption and noise immune coding

The subject matter of this article is the processes of increasing information security in communication systems to solve applied problems that are critical in the transmission of confidential data. The goal is to develop a multi-stage method for protecting information from unauthorized access, based on probabilistic encryption integration, error-correcting code, and error decorrelation. The tasks to be solved are as follows: to develop a probabilistic encryption algorithm that considers the entropy of the characters’ appearance in a message; to implement iterative coding with variable parameters of the information bits matrix; and to implement error decorrelation based on the generated matrix by interleaving information and check bits according to a given algorithm. Methodology: theory of signal communication and signal processing, theory of cryptography, theory of noise-resistant codes, probability theory, statistical analysis. The following results were obtained: a multi-stage method for protecting information from unauthorized access was proposed, in which at each step of data conversion, information secrecy is increased; probabilistic encryption was implemented, which considers the entropy of a discrete source of information when forming a space of random combinations; based on an iterative code with specified matrix parameters, an additional increase in the space of random combinations was implemented; error decorrelation reduces the multiplicity of errors in codewords and ensures mixing of bits according to a predetermined law. Conclusions. The scientific novelty of the results obtained is as follows: 1) an improved method of information protection from unauthorized access is proposed, based on probabilistic encryption integration, interference-resistant coding, and error decorrelation; 2) increasing information concealment is realized by eliminating the main shortcomings of probabilistic encryption, which did not take into account the entropy of the symbols of the open message; 3) it is proposed to form the space of random combinations taking into account the average probability of the appearance of a symbol in open texts, which will allow the output of a probabilistic cipher to form a stream of random combinations, which, according to its statistical properties, is close to the uniform distribution law; 4) further development of information protection methods based on interference-resistant coding and error decorrelation with encryption functions is received; 5) a further development of the statistical encryption method is the use of all redundant elements for both probabilistic encryption and interference-resistant coding.

A reversible and lossless secret image sharing scheme with authentication for color images

With the increasing concern for public privacy protection, Secret Image Sharing (SIS) has garnered significant attention among researchers. The goal of SIS is to split a secret image into multiple shadows, rendering it unrecoverable unless a specific threshold of shares is obtained. However, these shadows typically appear as meaningless noise-like patterns, making them susceptible to attacks and raising suspicion when transmitted over traditional internet channels. Moreover, traditional SIS schemes often restrict image formats to binary, limiting their applicability. To address these limitations, we propose a reversible and lossless secret image sharing scheme with authentication specifically designed for color images. Our scheme generates noise-like shadows by combining original secret images and authentication images, which are then embedded into color images using an enhanced steganography method. During the recovery process, participants can extract the shares losslessly and complete the authentication phase without the need for a trusted third party. The authentication results can be easily verified by visual inspection. Ultimately, the qualified shadows are utilized to reconstruct the secret image, ensuring secure transmission of confidential image data. The efficacy and security of our proposed method are demonstrated via theoretical analysis and experimental results.

High-Capacity Reversible Data Hiding Based on Two-Layer Embedding Scheme for Encrypted Image Using Blockchain

In today’s digital age, ensuring the secure transmission of confidential data through various means of communication is crucial. Protecting the data from malicious attacks during transmission poses a significant challenge. To achieve this, reversible data hiding (RDH) and encryption methods are often used in combination to safeguard confidential data from intruders. However, existing secure reversible hybrid hiding techniques are facing challenges related to low data embedding capacity. To address these challenges, the proposed research presents a solution that utilizes block-wise encryption and a two-layer embedding scheme to enhance the embedding capacity of the cover image. Additionally, this technique incorporates a blockchain-enabled RDH method to ensure traceability and integrity by storing confidential data alongside the hash value of the stego image. The proposed work is divided into three phases. First, the cover image is encrypted. Second, the data are embedded in the encrypted cover image using a two-layer embedding scheme. Finally, the stego image along with the hash value are deployed through blockchain technology. The proposed method reduces challenges associated with traceability and integrity while increasing the embedding capacity of images compared to traditional methods.

Initial point for enhancing DC Programming and DCA in Physical Layer Security

Abstract— Physical layer security (PLS) is to enable confidential data transmission through wireless communication systems in the presence of illegitimate receivers, without basing on higher-layer encryption. The goal of PLS is to make use of the properties of the physical to enable critical aspects of secure communication. PLS's additional strength is that it is based on information-theoretic security, which assumes no limit on the opponent's computational power and is thus inherently quantum-resistant. In general, PLS problems are non-convex programming and thus hard to deal with. One approach to handling these problems is based on DC programming and DCA, in which finding a good initial point of DCA scheme is still a complicated, challenging and open problem. This paper proposal some good initial points for the PLS problem DCA-DF scheme on Decode-and-Forward relaying wireless networks.

Deep learning based physical layer security for terrestrial communications in 5G and beyond networks: A survey

The key principle of physical layer security (PLS) is to permit the secure transmission of confidential data using efficient signal-processing techniques. Also, deep learning (DL) has emerged as a viable option to address various security concerns and enhance the performance of conventional PLS techniques in wireless networks. DL is a strong data exploration technique which can be used to learn normal and abnormal behavior of 5G and beyond wireless networks in an insecure channel paradigm. Also, since DL techniques can successfully predict future new instances by learning from existing ones, they can successfully predict new attacks, which frequently involve mutations of earlier attacks. Thus, motivated by the benefits of DL and PLS, this survey provides a comprehensive review that overviews how DL-based PLS techniques can be employed for solving various security concerns in 5G and beyond networks. The survey begins with an overview of physical layer threats and security concerns in 5G and beyond networks. Then, we present a detailed analysis of various DL and deep reinforcement learning (DRL) techniques that are applicable to PLS applications. We present the specific use-cases of PLS design for each type of technique, including attack detection, physical layer authentication (PLA), and other PLS techniques. Then, we present an in-depth overview of the key areas of PLS where DL can be used to enhance the security of wireless networks, such as automatic modulation classification (AMC), secure beamforming, PLA, etc. Performance evaluation metrics for DL-based PLS design are subsequently covered. Finally, we provide insights to the readers about various challenges and future research trends in the design of DL-based PLS for terrestrial communications in 5G and beyond networks.

PERFORMANCE OF SECURE COMMUNICATION OVER LAMBDA-FISHER-SNEDECOR FADING CHANNELS

In this paper, we investigate the physical layer security (PLS) of the traditional Wyner’s wiretap channel model. Secrecy performance analysis is performed assuming a presence of an active eavesdropper trying to overhear the confidential data transmission from the source node to the predefined destination. In what follows, we derive the lower bound of the secrecy outage probability, the strictly positive secrecy capacity as well as the average secrecy capacity, over the composite a-Fisher-Snedecor (a-F) fading environment. According to the analytical results, numerical results are also shown. The impact of the path loss component, the average signal-to-noise ratios over the main/wiretap channel as well as the impact of the fading, the non-linearity of the propagation medium and the shadowing shaping parameter on the PLS metrics is examined. The overall analysis and the obtained results have a high level of generality and also a high level of applicability since the a-F distribution was recently proposed, as the best fit distribution for the channel characterization of the device-to-device wireless communication in the future Beyond 5G networks.

BIOMEDICAL IMAGE AUGMENTATION AND TRANSMISSION USING STEGANOGRAPHY

Objective: The aim of the study was to embed sensitive patient information and image data in a cover image to enable secure transmission of confidential data. Methods: Image steganography is a process used to embed (hide with encryption) data which includes text, images or audio, and video files inside the main image file. This embedding is done by altering the values of some pixels which are chosen by the encryption algorithm. The algorithm used in this case is the Discrete Wavelet Transformation Algorithm using MATLAB. Results: Statistical features such as signal to noise ratio (SNR), Peak SNR, and (mean squared error) were extracted from the medical images to test the loss during steganography and transmission. Conclusion: A technique that enables secure and swift image data transmission using image steganography technique is proposed.

Development of tools for information protection of optical text recognition systems

The subject of research. There has been studying a new universal method of information protection in optical text recognition systems when transmitting confidential data over open communication channels. This work develops the concept of creating a modern, simple and reliable method for protecting information during its transmission over communication channels, to determine the objective criteria for the quality of its work, to create a set of algorithms for implementing the proposed method and software for conducting experimental studies. The current work puts on the concept of creation of a simple and reliable current method for protecting information when passing it through communication channels, also to define the objective criteria for assessing the tool operation quality and to exercise the dedicated programs, which implement the proposed methods and developed algorithms. Based on the results of these studies, it must evaluate the practice effectiveness of the proposed method in terms of both the transmitted data coding/decoding reliability and the secrecy of the fact of special information transmission. Results. It is described the universal concept of producing and use of the contemporary methods of information protection in optical text recognition systems in a confidential data transmission over open communication channels. The main criteria for these systems performance quality are determined. A new combined method for encrypting transmitted messages using QR-codes with subsequent masking of the fact of data transmission by various methods of LSB-steganography is proposed. To conduct experimental studies, a text recognition program based on Tesseract OCR software version 4.0 was developed. The program in Python uses the recent resources of the OpenCV library. The dedicated software technique contributed to assessing the efficiency of the algorithms, which realized the transmitted data encryption and therefore communication links privacy. There are examples of the system operation and results of the software testing in modes of messages encoding for subsequent hidden transmission. Conclusion. The case studies acknowledge the high efficiency of the proposed method of confidential data protection when transmitting them via open networks. The technique can be taken as a basis for developing software aimed at protecting information in OCR systems offered by various manufacturers.

Lightweight Security Transmission in Wireless Sensor Networks through Information Hiding and Data Flipping.

Eavesdroppers can easily intercept the data transmitted in a wireless sensor network (WSN) because of the network’s open properties and constrained resources. Therefore, it is important to ensure data confidentiality in WSN with highly efficient security mechanisms. We proposed a lightweight security transmission method based on information hiding and random data flipping to ensure that the ally fusion center (AFC) can achieve confidential data transmission over insecure open links. First, the sensors’ local measurements are coded into a customized binary string, and then before data transmission, some parts of the string are flipped by the sensors according to the outputs of a pre-deployed pseudo-random function. The AFC can recover the flipped binaries using the same function and extract the measurement hidden in the string, while the enemy fusion center (EFC) cannot distinguish flipped and non-flipped data at all, and they cannot restore the measurement correctly as long as one bit in the string is not correctly recovered. We proved the security and anti-interference of the scheme through both simulations and physical experiments. Furthermore, the proposed method is more efficient such that it consumes less power than traditional digital encryptions through real power consumption tests.

Efficient Cost-Reduced With High-Quality Image of Imperceptible Steganography Using Modulo and Magic Cube

Information hiding techniques are used to hide confidential data in digital carriers. It is difficult for malicious users to detect the existence of confidential data within the digital carriers. Audios, images, or videos can call be digital carriers. Information hiding includes steganography and watermarking. Watermarking is used for copyright protection. Steganography is used to protect confidential data transmission from malicious attackers. Imperceptibility and capacity are always the major concerns in steganography. In this paper, we propose an efficient steganography method for images using modulus operation and magic cube. The partial secret message bits are converted into decimals and then mapped to a predefined cube. The coordinates of the mapped position were embedded into the cover image using modulus operation. We obtain the stego-image quality better than 42 dB, while the payload is 3 bpp. The experimental results demonstrated that the proposed method has a higher capacity than previous works. Meanwhile, our method also maintain high imperceptibility. Furthermore, modulus operation can reduce the computational overhead of the proposed method.

Efficient network selection using multi fuzzy criteria for confidential data transmission in wireless body sensor networks

In the last decade, due to wireless technology’s enhancement, the people’s interest is highly increased in Wireless Body Sensor Networks (WBSNs). WBSNs consist of many tiny biosensor nodes that are continuously monitoring diverse physiological signals such as BP (systolic and diastolic), ECG, EMG, SpO2, and activity recognition and transmit these sensed patients’ sensitive information to the central node, which is straight communicate with the controller. To disseminate this sensitive patient information from the controller to remote Medical Server (MS) needs to be prolonged high-speed wireless technology, i.e., LTE, UMTS, WiMAX, WiFi, and satellite communication. It is a challenging task for the controller to choose the optimal network to disseminate various patient vital signs, i.e., emergency data, normal data, and delay-sensitive data. According to the nature of various biosensor nodes in WBSNs, monitor patient vital signs and provide complete intelligent treatment when any abnormality occurs in the human body, i.e., accurate insulin injection when patient sugar level increased. In this paper, first, we select the optimal network from accessible networks using four different fuzzy attribute-based decision-making techniques (Triangular Cubic Hesistent Fuzzy Weighted Averaging Operator, Neutrosophic Linguistic TOPSIS method, Trangualar Cubic Hesistent Fuzzy Hamacher Weighted Averaging Operator and Cubic Grey Relational Analysis) depending upon the quality of service requirement for various application of WBSNs to prolong the human life, enhanced the society’s medical treatment and indorse living qualities of people. Similarly, leakage and misuse of patient data can be a security threat to human life. Thus, confidential data transmission is of great importance. For this purpose, in our proposed scheme, we used HECC for secure key exchange and an AES algorithm to secure patient vital signs to protect patient information from illegal usage. Furthermore, MAC protocol is used for mutual authentication among sensor nodes and Base Stations (BS). Mathematical results show that our scheme is efficient for optimal network selection in such circumstances where conflict arises among diverse QoS requirements for different applications of WBSNs.

A New Combinational Technique in Image Steganography

Internet is used for exchanging information. Sometimes it is needed to transmit confidential data via internet. Here the authors use image steganography to pass confidential data within a cover image. To construct the algorithm, they take the combinational help of particle swarm optimization (PSO), bi-orthogonal wavelet transform (BWT), and genetic algorithm (GA). They use PSO to take the enhanced version of cover image. They use BWT to choose the selective sub bands of cover image and we utilize GA to select a particular stego image among a set of stego images. Thus, an innovative technique of image steganography has been made to transmit confidential data via cover image generating stego image. This combinational approach of image steganography is quite safe for confidential data transmission and makes it hard for the attackers to retrieve the confidential data.

Discrete Cosine Transform-Domain Based Video Steganography using Multiple Object Tracking

In the current era, the need for transmission of confidential data is pivotal in all domains of technology. New methodologies are being proposed for this very purpose, each being developed on specific shortcomings of previously proposed methods. In this paper, one such method for embedding and communicating confidential information has been proposed which employs encryption and error correction algorithms to further improve the reliability and robustness of the system. First, the information is preprocessed by encrypting the text using RC4 algorithm. The encrypted text is processed using hamming codes (4,7) to improve its reliability. After the pre-processing stage, the video is processed to identify reliable motion regions using the MOT (Multiple Object Tracking) algorithm. The identified regions are used to embed the confidential text by calculating its DCT coefficients and manipulating its values to embed the information. The non-motion region is used to store the key used during the pre-processing stage. This completes the processes at the transmitter’s part. The inverse of the process-extraction and decoding is applied at the receiver’s side to retrieve the confidential piece of information being transferred. The proposed methodology further focusses on comparing the visual quality and hiding capacity achieved by adopting DCT and DWT algorithms, to determine the better of the two frequency domain techniques in steganographic applications.

GA based Feature Selection for Multimodal Biometric Authentication

Multi-modal biometric authentication effectively replaces uni-modal biometric authentication system towards addressing a wide range of technical glitches in identity management and authentication. Legitimacy is playing a vital role in banking, military, and healthcare sectors where highly secure, strategic and confidential data transmission is involved. By integrating many independent biometric systems, one can overcome the problems of spoofing. However, there is lack of a simple, efficient and sufficient biometric authentication. Hence, the present study focuses on designing and implementing a multi-modal biometric authentication using a Genetic Algorithm (GA) based feature extraction method. The proposed research focuses on extracting human Skeleton and Human face feature using 3D Imaging technology. This modelling technique is used to capture human joints including the depth data to improve the efficiency of the system. The proposed research is subdivided into three phases. These are, image preprocessing (MinMax method), feature extraction using Heuristic Optimization Techniques (HOT), and Personnel recognition via the Artificial Neural Network (ANN). The Performance of the proposed method is evaluated based on the measure of FAR, FRR and accuracy. Finally, the performance of proposed approach is compared with existing techniques like GA, Neural network, etc. Combined Biometric is done in an unobtrusive way whereas other human recognition needs physical contact.

Intelligent Mobile Edge Computing Networks for Internet of Things

In this work, an intelligent mobile edge computing (MEC) network is studied for Internet of Things (IoT) in the presence of eavesdropping environments, where there are multiple users who can offload their confidential tasks to the computational access point (CAP) for the assistance of computation. One unmanned aerial vehicle (UAV) attacker exists in the system and it can listen to the confidential data transmission from the users to the CAP. We optimize the system design of the intelligent MEC network, by adaptively allocating the offloading ratio and wireless bandwidth, to reduce the linearly weighted cost of the latency as well as energy consumption (EnC). Specifically, starting from the deep reinforcement learning, we devise a deep Q-network (DQN) network to adjust the offloading ratio and transmission bandwidth, which can help calculate the computational tasks and suppress the eavesdropping from the UAV efficiently. We finally provide some simulation results to validate the proposed offloading strategy. In particular, the proposed offloading strategy can achieve a much lower cost compared to the conventional ones, in the terms of latency and EnC.

Trust-based secure directed diffusion routing protocol in WSN

Deployed in the monitoring environment, Wireless Sensor Network (WSN) is a measurement and control network composed of miniature and low-cost sensors with sensing, computing, and communication capabilities. The design of the Directed Diffusion (DD) routing protocol is one of the key problems in WSN. In order to obtain the confidentiality of sensing data and solve the unreliability of relay nodes in the existing DD routing protocols, this paper designs an Energy Trust Model (ETM) by introducing the remaining energy and trust of a node. We further propose a Trust-based Secure Directed Diffusion Routing protocol (TSDDR) based on the model. The proposed protocol achieves the establishment of a credible communication path and the transmission of confidential data in WSN. Meanwhile, the balance of energy consumption and the privacy of sensing data can be ensured. The performance analysis results show that the TSDDR protocol can effectively defeat against MITM attacks and prevent the malicious nodes’ impersonation. At the same time, the protocol achieves secure end-to-end anonymous communication with acceptable energy overhead and computational complexity.

Stable and Highly Efficient Free-Space Optical Wireless Communication System Based on Polarization Modulation and In-Fiber Diffraction

The performance of free-space optical data transmission is severely deteriorated by the fluctuation of optical signal intensity, which is resulted from the bias drift of electro-optical modulation devices. In order to improve the performance of free-space optical communication systems, a bias-drift avoiding, beam steered free-space optical wireless communication system is presented based on polarization modulation for the first time to the best of our knowledge. An in-fiber diffraction device based on a 45° tilted fiber grating (TFG) serves simultaneously as an in-fiber polarizer, free-space light emitter, and beam steerer in the proposed communication system, which endows the proposed system with the merits of highly efficient, compact, stable and bias-drift free. The usage of 45° TFG has three benefits: 1), it realizes polarization modulation preventing bias-drift due to its polarization sensitive feature; 2), it enables stable and highly efficient in-fiber compact free-space light emitter; and 3) it accomplishes free-space beam steering due to its wavelength-depending diffraction characteristic. A 2.1 m free-space optical wireless data transmission has been demonstrated with a data rate of 4.8 Gbps per beam using 1.2 GHz bandwidth OFDM signals. This proposal prevents the bias drift issue and maintains high stability. Hence, it can be applied in some harsh situations and confidential data transmission fields.