Secure Data Transmission Research Articles

SAC-based UAV mobile edge computing for energy minimization and secure data transmission

In recent years, the use of UAVs to carry mobile edge computing servers has become an emerging solution to the problem of collaborative ground-to-air communication. However, due to the limited energy consumption of UAVs and the open nature of wireless communication, UAV-based mobile edge computing faces issues such as limited operation time and the potential for insecure connections during data transmission. In this paper, we model a secure data transmission model for UAVs with the goal of minimizing energy consumption. First, we decompose the system energy consumption optimization problem into two sub-problems: ground user energy consumption overhead and UAV energy consumption overhead. We consider the limitations of UAV flight range, computational power, and transmission capability in relation to ground user and UAV, solve the energy consumption optimization problem by deep reinforcement learning, and propose a solution based on the SAC algorithm. The solution applies the idea of maximum entropy to explore the optimal policy and use efficient iterative updates to obtain the optimal policy, enhancing the exploration capability of the algorithm and improving the convergence speed of the training process by retaining all policies with high return values. Secondly, considering the existence of insecure connection nodes in practical application scenarios, a ground user data protection scheme based on Paillier encryption and blockchain is used to achieve secure data transmission. Simulation results show that the proposed method can achieve secure data offloading, effectively reduce the average energy consumption of users, and have good stability and convergence compared with existing methods.

Transformative synergy: SSEHCET—bridging mobile edge computing and AI for enhanced eHealth security and efficiency

Blockchain technologies (BCT) are utilized in healthcare to facilitate a smart and secure transmission of patient data. BCT solutions, however, are unable to store data produced by IoT devices in smart healthcare applications because these applications need a quick consensus process, meticulous key management, and enhanced eprivacy standards. In this work, a smart and secure eHealth framework SSEHCET (Smart and Secure EHealth Framework using Cutting-edge Technologies) is proposed that leverages the potentials of modern cutting-edge technologies (IoT, 5G, mobile edge computing, and BCT), which comprises six layers: 1) The sensing layer-WBAN consists of medical sensors that normally are on or within the bodies of patients and communicate data to smartphones. 2) The edge layer consists of elements that are near IoT devices to collect data. 3) The Communication layer leverages the potential of 5G technology to transmit patients' data between multiple layers efficiently. 4) The storage layer consists of cloud servers or other powerful computers. 5) Security layer, which uses BCT to transmit and store patients' data securely. 6) The healthcare community layer includes healthcare professionals and institutions. For the processing of medical data and to guarantee dependable, safe, and private communication, a Smart Agent (SA) program was duplicated on all layers. The SA leverages the potential of BCT to protect patients' privacy when outsourcing data. The contribution is substantiated through a meticulous evaluation, encompassing security, ease of use, user satisfaction, and SSEHCET structure. Results from an in-depth case study with a prominent healthcare provider underscore SSEHCET's exceptional performance, showcasing its pivotal role in advancing the security, usability, and user satisfaction paradigm in modern eHealth landscapes.

A control scheme for interval type‐2 T‐S fuzzy systems at constrained bit rates: A coding and decoding scheme

SummaryThis study focuses on a class of interval type‐2 T‐S fuzzy systems under bit rate constraint(BRC), which can adapt to complex systems more flexibly than the traditional interval type‐1 T‐S fuzzy model. In order to guarantee the security of data transmission, and considering that the channel is affected by the bit rate during transmission, this study introduces a codec scheme in the interval type‐2 T‐S fuzzy system and applies it to the channel from the sensor to the controller. With the support of the codec scheme, this study explores the sufficient conditions to satisfy the data recoverability, and based on the satisfaction of these conditions, the system is proposed to satisfy the sufficient conditions for input‐to‐state stability (ISS) and the controller gain. Through the in‐depth analysis in this paper, this study proposes a control scheme that can fit complex systems more accurately and also confirms the importance of considering bit rate constraints in communication systems. Finally, the paper is validated by simulation with two specific examples, which fully demonstrate the superiority and effectiveness of the proposed control scheme.

A Hybrid Cryptographic Mechanism for Secure Data Transmission in Edge AI Networks

As Edge AI systems become more prevalent, ensuring data privacy and security in these decentralized networks is essential. In this work, a novel hybrid cryptographic mechanism was presented by combining Ant Lion Optimization (ALO) and Diffie–Hellman-based Twofish cryptography (DHT) for secure data transmission. The developed work collects the data from the created edge AI system and processes it using the Autoencoder. The Autoencoder learns the data patterns and identifies the malicious data entry. The Diffie–Hellman (DH) key exchange generates a shared secret key for encryption, while the ALO optimizes the key exchange and improves security performance. Further, the Twofish algorithm performs the data encryption using a generated secret key, preventing security threats during transmission. The implementation results of the study show that it achieved a higher accuracy of 99.45%, lower time consumption of 2 s, minimum delay of 0.8 s, and reduced energy consumption of 3.2 mJ.

Data transmission via hybrid fuzzy time slot scheduling in long-range communication

ABSTRACT Several communication protocols have been tuned for LoRaWAN since the development of LoRa technology more than 10 years ago. LPWAN technology can address issues like overlooked delivery ratio, reducing low frequency and limited data availability, thereby improving system effectiveness, and enormous packet drops due to collisions will exist. Hence the hybrid fuzzy time slot scheduling is proposed to avoid collision in the packet with secure data transmission in the LoRa communication. The fuzzy C means clustering algorithm is suggested to cluster nodes and select the Cluster head based on distance and energy usage. The packet transmission is carried out using the time slot scheduling mechanism by TDMA, which sends the packet without collision. The proposed hybrid method can improve data transmission reliability by minimising collisions, optimising time slots, improving network capacity and decreasing idle time. The outcomes reveal that the proposed hybrid method attains high bandwidth with frequency, throughput and PDR also the PLR attains low without collision of a packet received when related to other prior techniques.

A Novel Cloud-Based IoT Framework for Secure Health Monitoring

The growing use of Internet of Things (IoT) technologies in a variety of sectors, including healthcare, has opened up new possibilities for gathering and analyzing patient data. In some cases, the elderly are exposed to significant risk and even mortality as a result of the global aging problem, which has become a burden in recent years. Numerous IoT devices are being created to monitor, track, and record the actions of the elderly to reduce these hazards. This study proposed a novel, dependable, cloud-based remote system patient monitoring framework for IoT health detection. The main distinguished part of this research is that we rarely can find a framework in the literature that is based on real-time systems by considering heartbeat (BPM), blood oxygen (SpO2), and body temperature at the same time. The implementation and testing of this real-time system is classified into six distinctly separated phases for developing both the hardware and software. To verify the performance of the suggested system, data were gathered from BOT-IoT datasets. The outcome enhances patient satisfaction, secure data transmission, and healthcare outcomes by showing that the proposed framework is more efficient than other compared protocols in terms of the decision time, which is 16.3 seconds for 46 features, with 100% accuracy.

Financial Anti-Fraud Based on Dual-Channel Graph Attention Network

This article addresses the pervasive issue of fraud in financial transactions by introducing the Graph Attention Network (GAN) into graph neural networks. The article integrates Node Attention Networks and Semantic Attention Networks to construct a Dual-Head Attention Network module, enabling a comprehensive analysis of complex relationships in user transaction data. This approach adeptly handles non-linear features and intricate data interaction relationships. The article incorporates a Gradient-Boosting Decision Tree (GBDT) to enhance fraud identification to create the GBDT–Dual-channel Graph Attention Network (GBDT-DGAN). In a bid to ensure user privacy, this article introduces blockchain technology, culminating in the development of a financial anti-fraud model that fuses blockchain with the GBDT-DGAN algorithm. Experimental verification demonstrates the model’s accuracy, reaching 93.82%, a notable improvement of at least 5.76% compared to baseline algorithms such as Convolutional Neural Networks. The recall and F1 values stand at 89.5% and 81.66%, respectively. Additionally, the model exhibits superior network data transmission security, maintaining a packet loss rate below 7%. Consequently, the proposed model significantly outperforms traditional approaches in financial fraud detection accuracy and ensures excellent network data transmission security, offering an efficient and secure solution for fraud detection in the financial domain.

Effective data transmission through energy-efficient clustering and Fuzzy-Based IDS routing approach in WSNs

Wireless sensor networks (WSN) gather information and sense information samples in a certain region and communicate these readings to a base station (BS). Energy efficiency is considered a major design issue in the WSNs, and can be addressed using clustering and routing techniques. Information is sent from the source to the BS via routing procedures. However, these routing protocols must ensure that packets are delivered securely, guar- anteeing that neither adversaries nor unauthentic individuals have access to the sent information. Secure data transfer is intended to protect the data from illegal access, damage, or disruption. Thus, in the proposed model, secure data transmission is developed in an energy-effective manner. A low-energy adaptive clustering hierarchy (LEACH) is developed to efficiently transfer the data. For the intrusion detection systems (IDS), Fuzzy logic and artificial neural networks (ANNs) are proposed. Initially, the nodes were randomly placed in the network and initialized to gather information. To ensure fair energy dissipation between the nodes, LEACH randomly chooses cluster heads (CHs) and allocates this role to the various nodes based on a round-robin management mechanism. The intrusion-detection procedure was then utilized to determine whether intruders were present in the network. Within the WSN, a Fuzzy interference rule was utilized to distinguish the malicious nodes from legal nodes. Subsequently, an ANN was employed to distinguish the harmful nodes from suspicious nodes. The effectiveness of the proposed approach was validated using metrics that attained 97% accuracy, 97% specificity, and 97% sensitivity of 95%. Thus, it was proved that the LEACH and Fuzzy-based IDS approaches are the best choices for securing data transmission in an energy-efficient manner.

Evaluation of the performance of the vehicular ad hoc network protocols in the case of V2I and EV2I communications

Vehicular ad hoc network (VANET) is an intelligent technology that enables efficient communication, secure data transmission, and traffic management. The purpose of routing protocols in the VANET network is to route data between vehicles (V2V) and vehicles-to-infrastructure (V2I). Recently, researchers have shown interest in designing effective routing protocols for the VANET network, as not all existing protocols are suitable for all traffic scenarios. Electric vehicles (EVs) are increasingly being adopted and integrated into intelligent transportation systems (ITS). Developed countries are actively promoting sustainable transportation solutions to increase energy efficiency and reduce carbon emissions. Therefore, this research presents an EV charging station (CS) management scheme based on communication between EVs and RSUs, with performance evaluation simulated using VANET network protocols. In this study, the G-MDORA, MDORA, and geographical routing protocol (GRP) protocols were modified to accommodate V2I communication, and RSUs were distributed along the roadmap. Additionally, a scheme for managing electric vehicle CS was presented, focusing on the communication between electric vehicles and RSUs in the EV2I context. Performance was evaluated using the G-MDORA, GRP, and MDORA protocols, considering factors such as throughput, communication overhead, packet delivery ratio, and end to end delay.

Secure and Energy-Aware Data Transmission for IoT-WSNs with the Help of Cluster-Based Secure Optimal Routing

Secure and Energy-Aware Data Transmission for IoT-WSNs with the Help of Cluster-Based Secure Optimal Routing

Application solutions of highway freight information systems based on quantum communication.

To improve the security of data transmission in the highway freight information system, this study is an application plan for the highway freight information system based on quantum communication. This solution is based on quantum communication technology to encrypt and transmit key sensitive data[1]; it realizes unified management of quantum keys through the quantum key cloud terminal and provides key services for the highway freight information system; it realizes access to the system through the quantum key cloud service platform. The secure use of mobile terminal quantum keys improves the overall security of the road freight information system. This scheme uses the quantum encryption key generated only once, effectively protecting the entire system's security. The quantum key management server and quantum key cloud platform defined in this plan manage terminals and quantum keys respectively, and jointly produce and distribute quantum keys with the help of other hardware facilities and software to provide secure transmission of key information.

Efficient Pairing-Free Certificateless Signcryption Scheme for Secure Data Transmission in IoMT

Efficient Pairing-Free Certificateless Signcryption Scheme for Secure Data Transmission in IoMT

Efficient color image steganography based on new adapted chaotic dynamical system with discrete orthogonal moment transforms

In today's rapidly evolving digital landscape, safeguarding the secure transmission of sensitive information is paramount. Traditional steganography methods, while effective at data concealment, have grown vulnerable to brute force attacks in our age of powerful computing. This paper addresses the pressing need to bolster data transmission security. To address the challenges posed by limited key space and security concerns associated with 1-D chaotic maps in data transmission, we introduce a novel 1-D chaotic map, the Multi-Parameter Chebyshev Map (MCM). The MCM boasts four control parameters, each with a broad chaotic range and high chaos level, significantly enhancing security. Furthermore, we present an innovative steganography technique for color images that leverages the MCM in conjunction with discrete moment transforms. This method chaotically embeds the secret message within the moment coefficients of a cover color image using MCM and quantization rules. The expansive chaotic range and high chaos level of the MCM substantially reinforce the security of this approach. The considered moment transforms include Tchebichef, Krawtchouk, Hahn, Charlier, Meixner, Shmaliy, Racah, and Dual-Hahn. The performance of the proposed steganography method is thoroughly evaluated and compared with other state-of-the-art methods in terms of hiding capacity and image quality in both spatial and transform domains. The quantization of moment coefficients demonstrates its superior performance. This method holds crucial implications for practical applications requiring secure communication of color images, such as military and medical contexts. The combination of MCM and moment transforms in this method presents a promising avenue for future research in the field of information hiding.

A review of IoT security and privacy using the Blockchain to Boost Data Integrity and Privacy

The Internet of Things (IoT) is an emerging technology. It enables users to exchange their data and resources by linking devices across the IoT network, resulting in a more relaxed and connected lifestyle. It allows real-time data to be delivered to end-user applications and systems via sensing, actuation, communication, computing, networking, and storage. It can transfer data across a network without requiring human intervention or computer-to-computer interaction. It makes it possible to detect the various sensors around the world through low-priced sensor devices. IoT Networking defines communication or inter-connection between Peer-to-Peer (P2P) either through a connected medium (Wired) or unconnected medium (Wireless) to procure a secure transmission of data. Blockchain is a peer-to-peer network where peers can communicate and do transactions without the need for centralized authority. It allows data to be stored and transferred in a safe and interconnected method. This section includes a literature review on the centralized IOT system model, highlighting the limitations of the centralized IoT system and blockchain security in IoT. This research study's systematic evaluation is processed based on the reviews of the literature available with recent advancements and inventions through patents, articles, conference papers, and journals. Also, the related work with IoT systems for data privacy and security issues and applying Blockchain technology to IOT are discussed.

An architectural framework of elderly healthcare monitoring and tracking through wearable sensor technologies

The growing elderly population in smart home environments necessitates increased remote medical support and frequent doctor visits. To address this need, wearable sensor technology plays a crucial role in designing effective healthcare systems for the elderly, facilitating human–machine interaction. However, wearable technology has not been implemented accurately in monitoring various vital healthcare parameters of elders because of inaccurate monitoring. In addition, healthcare providers encounter issues regarding the acceptability of healthcare parameter monitoring and secure data communication within the context of elderly care in smart home environments. Therefore, this research is dedicated to investigating the accuracy of wearable sensors in monitoring healthcare parameters and ensuring secure data transmission. An architectural framework is introduced, outlining the critical components of a comprehensive system, including Sensing, Data storage, and Data communication (SDD) for the monitoring process. These vital components highlight the system's functionality and introduce elements for monitoring and tracking various healthcare parameters through wearable sensors. The collected data is subsequently communicated to healthcare providers to enhance the well-being of elderly individuals. The SDD taxonomy guides the implementation of wearable sensor technology through environmental and body sensors. The proposed system demonstrates the accuracy enhancement of healthcare parameter monitoring and tracking through smart sensors. This study evaluates state-of-the-art articles on monitoring and tracking healthcare parameters through wearable sensors. In conclusion, this study underscores the importance of delineating the SSD taxonomy by classifying the system's major components, contributing to the analysis and resolution of existing challenges. It emphasizes the efficiency of remote monitoring techniques in enhancing healthcare services for the elderly in smart home environments.

LW-PWECC: Cryptographic Framework of Attack Detection and Secure Data Transmission in IoT

In the present era, the number of Internet of Health Things (IoHT) devices and applications has drastically expanded. Security and attack are major issues in the IoHT domain because of the nature of its architecture and sorts of devices. Over the recent few years, network attacks have dramatically increased. Many detection and encryption techniques are existing however they lack accuracy, training stability, insecurity, delay etc. By the above concerns, this manuscript introduces a novel deep learning technique called Agnostic Spiking Binarized neural network with Improved Billiards optimization for accurate detection of network attacks and Light Weight integrated Puzzle War Elliptic Curve Cryptographic framework for secure data transmission with high security and minimal delay. Optimal features from the datasets are selected by volcano eruption optimization algorithm with better convergence for reducing the overall processing time. Wilcoxon Rank Sum and Mc Neymar’s tests are performed for proving the statistical analyses. The outcomes show that the introduced approach performs with an overall accuracy of 99.93% which is better than the previous techniques demonstrating the effectiveness.

Safeguarding Software-Defined Networks: Comprehensive Frameworks and Best Practices for Security Threat Mitigation

Abstract: The proliferation of IoT devices such as sensors, actuators, sensors, and other endpoints has resulted in a significant surge in data generation. Ensuring the security and efficiency of data transmission necessitates the implementation of an internet design that possesses the capability to scale as required. This study investigates the potential impact of SDN on enhancing the performance of IoT networks. This study examines the ability to adapt network resources in real-time to meet the demands of IoT applications. It is imperative to address the security vulnerabilities in the SDN architecture to ensure secure and reliable network operations. This paper thoroughly examines the challenges, various security solutions, and recommended practices for effectively protecting SDN infrastructures. This study comprehensively analyzes the pertinent scholarly works, conducts a comparative analysis of diverse security approaches, and assesses their respective advantages and limitations. The need for further investigation into the security aspects of SDN is also acknowledged. This article highlights the importance of enhancing security practices, implementing continuous monitoring, and identifying potential threats. Additionally, it presents case studies that exemplify real-world security challenges associated with SDN. Further, this study incorporates security solutions into SDN frameworks, emphasizing the significance of meticulous strategic preparation, comprehensive testing, and ongoing upkeep to ensure seamless interoperability with current systems. This study is significant as it contributes to the expanding literature on security in SDN. The comprehensive examination of existing literature, meticulous analysis, thorough review of security approaches, identification of issues and limitations, and exploration of potential avenues for future research in this work render it a valuable resource for researchers and practitioners investigating SDN security. The primary objective of this study is to improve the reproducibility and pragmatic assessment of security measures in SDN settings. This study provides comprehensive information on implementation, testbed settings, datasets, and experimental procedures to promote transparency and repeatability. The study presents findings from extensive testing and benchmarking, showcasing the effectiveness of security solutions in addressing different types of threats. The study focuses on achieving a harmonious equilibrium between accuracy and efficient utilization of resources. The primary objective of this study is to improve the reproducibility and pragmatic assessment of security measures in SDN settings. This study includes comprehensive information on implementation, testbed configuration, datasets, and experimental procedures to promote transparency and reproducibility. The study presents empirical evidence and analysis to support the effectiveness of security solutions in addressing different types of threats. It specifically focuses on achieving a trade-off between accuracy and efficient use of resources.

An anonymous authentication and secure data transmission scheme for the Internet of Things based on blockchain

An anonymous authentication and secure data transmission scheme for the Internet of Things based on blockchain

Synchronization of Analog-Discrete Chaotic Systems for Wireless Sensor Network Design

The current work is focused on studying the performance of the Pecora–Carroll synchronization technique to achieve synchronization between the analog and discrete chaos oscillators. The importance of this study is supported by the growing applications of chaotic systems for improving the security of data transmission in various communication layers, primarily on the physical layer. The hybrid analog-discrete approach of implementing chaos oscillators opens new possible communication schemes for wireless sensor network (WSN) applications. The analog implementation of chaos oscillators can benefit the simpler sensor node (SN) integration, while the discrete implementation can be used on the gateway. However, the core of such chaos-based communications is synchronizing analog and discrete chaos oscillators. This work studies two key parameters of analog-discrete chaotic synchronization: chaotic synchronization noise immunity and synchronization speed. The noise immunity study demonstrates the quality of synchronization at various noise levels, while the synchronization speed demonstrates how quickly the analog-discrete synchronization is achieved, along with how quickly the two systems diverge when synchronization is no longer present. The two studies use both simulation-based and hardware-based approaches. In the simulation case, the analog oscillator’s circuit is modeled in LTspice XVII, while in the hardware case, the circuit is implemented on the PCB. In both simulation and hardware studies, the discrete model of the oscillator is implemented in MATLAB R2023b. The studies are performed for two pairs of different chaos oscillators to widen the proposed approach application potential: the Vilnius and RC chaos oscillators. The oscillators have been selected due to their simplicity and similar dynamic behavior for model-based and electrical circuit implementation. The proposed approach also allows us to compare the synchronization of different oscillators in the analog-discrete implementation.

IfNot: An approach towards mitigating interest flooding attacks in Named Data Networking of Things

Named Data Networking (NDN) has emerged as a model to accommodate content distribution, security, and mobility. Recently, NDN has been applied to the Internet of Things (IoT), referred to as Named Data Networking of Things (NDNoT). In the rapidly evolving landscape of the NDNoT securing data transmission is paramount. The main purpose and contribution of the research presented in this paper is to safeguard the security vulnerabilities of data transmission in NDNoT. This paper specifically addresses the critical issue of interest flooding attacks in NDNoT. These attacks can disrupt network operations posing far-reaching threats to data integrity and availability. To mitigate these attacks and threats the paper introduces the IfNoT mechanism and evaluates its performance through comprehensive simulations in a realistic and recognized simulator, called Cooja. IfNot identifies the potential interest flooding attacker nodes in the NDNoT environment. It reduces the impact of the attack and the undesirable interest traffic caused by such an attack, which optimizes the network resource utilization at a maximum level. The study also explores the influence of key parameters provided by the IfNoT mechanism. Moreover, the study also identifies optimum settings for these parameters to enhance network utilization. When evaluated using various metrics, including success rate, average latency, and total interest traffic, under different conditions and parameter settings, IfNoT was able to counter the interest flooding attacks effectively. IfNoT mechanism is able to increase success ratio up to 28%, decrease average latency up to 31%, and decrease total interest traffic up to 58%.