Secure Data Transmission Research Articles

Robust Color Image Encryption Scheme Based on RSA via DCT by Using an Advanced Logic Design Approach

Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to a subsystem consisting of an Reversible Logic Gate (RLG) group to obtain the secret keys that are passed to Rivest Shamir Adleman (RSA) to finish encrypting the image. The results indicate that the proposed method has the ability to generate a very large set of highly complex and secure secret keys that can be used later in the encryption stage. Moreover, the number and complexity of those keys will change each time the image is changed, and this represents the contribution of the proposed method. They experienced no time loss throughout the encryption and decryption processes when using RLG, which indicates that the proposed system did a good job in making different keys from the same image. And it differs in the strength of the key from one image to another, depending on the nature of the color imge.

Enhancing Network Security: A Robust Network Access Control and Authentication Mechanism for Secure Data Transmission

In an era dominated by digital communication and networked systems, the imperative to secure data transmission is more critical than ever. This paper introduces a cutting-edge Network Access Control (NAC) and authentication mechanism aimed at fortifying the security of data transmission across networks. Leveraging advanced technologies such as biometric authentication, multi-factor authentication (MFA), and anomaly detection, the proposed mechanism establishes a robust line of defense against unauthorized access and evolving cyber threats. Drawing on a comprehensive review of literature, real-world case studies, and practical implementations, this paper substantiates the efficacy and feasibility of the proposed approach. The integration of innovative security protocols serves to address the vulnerabilities inherent in traditional access control systems, contributing to a dynamic and proactive network security paradigm.

LELBC: A low energy lightweight block cipher for smart agriculture

The massive collection and transmission of various crop and livestock data in smart agriculture leads to serious security concerns. Furthermore, many Internet of Things (IoT) devices in smart agriculture are battery-powered, with limited energy resources. Therefore, a low energy lightweight block cipher (LELBC) is proposed to overcome the data leakage problem during sensor data transmission in smart agriculture. Firstly, a new permutation substitution permutation (PSP) structure is proposed, taking into account the energy resource constraints of unified encryption and decryption (ED) circuits. It has highly consistent encryption and decryption and a good diffusion effect. Secondly, a 4-bit low energy involutive S-box is obtained based on a genetic algorithm. The proposed S-box has lower area and latency compared to the existing S-boxes. The experimental data show that LELBC consumes 1864 gate equivalents (GE) in area and 6.99 μJ/bit in energy (encryption + decryption) under the UMC 0.18μm 1P6M process library. LELBC decreases energy and area consumption by 24.02% and 24.04%, respectively, compared to Midori. Finally, a temperature collection and encryption transmission platform is established. LELBC is deployed on the platform to encrypt the collected data, establishing the first line of defense for the secure transmission of smart agriculture sensor data.

Authentication in Peer-to-Peer Cloud using AES and SRP

The system focuses on proposing a robust authentication framework based on these Secure Remote Password (SRP) protocol to enhance the security of data exchange in Peer-to- Peer (P2P) cloud environments. The Advanced Encryption Standard (AES) algorithm provides encryption and the SRP protocol leverages cryptographic primitives to establish mutual authentication between cloud servers and users, ensures that data, remains protected against any vulnerabilities. The system encompasses various stages, including user registration, key establishment, and secure data transmission. After user registration, the SRP protocol employs a zero-knowledge proof mechanism to maintain the security of data available on cloud servers, mitigating the risks associated with password leaks and unauthorized access. Furthermore, the protocol facilitates secure key exchange to establish a confidential communication channel between peers, enabling encrypted data transmission. The system integrates SRP protocol and AES encryption, fortifying data security in P2P cloud environments through robust authentication, ensuring a comprehensive defence against potential vulnerabilities.

F-CAPSO: Fuzzy chaos adaptive particle swarm optimization for energy-efficient and secure data transmission in MANET

F-CAPSO: Fuzzy chaos adaptive particle swarm optimization for energy-efficient and secure data transmission in MANET

Quantum walks-based simple authenticated quantum cryptography protocols for secure wireless sensor networks

Wireless sensor networks (WSNs) play a crucial role in various applications, ranging from environmental monitoring to industrial automation that require high levels of security. With the development of quantum technologies, many security mechanisms may be hacked due to the promising capabilities of quantum computation. To address this challenge, quantum protocols have emerged as a promising solution for enhancing the security of wireless sensor communications. One of the common types of quantum protocols is quantum key distribution (QKD) protocols, which are investigated to allow two participants with fully quantum capabilities to share a random secret key, while semi-quantum key distribution (SQKD) protocols are designed to perform the same task using fewer quantum resources to make quantum communications more realizable and practical. Quantum walk (QW) plays an essential role in quantum computing, which is a universal quantum computational paradigm. In this work, we utilize the advantages of QW to design three authenticated quantum cryptographic protocols to establish secure channels for data transmission between sensor nodes: the first one is authenticated quantum key distribution (AQKD), the second one is authenticated semi-quantum key distribution (ASQKD) with one of the two participants having limited quantum capabilities, and the last one is ASQKD but both legitimate users possess limited quantum resources. The advantages of the proposed protocols are that the partners can exchange several different keys with the same exchanged qubits, and the presented protocols depend on a one-way quantum communication channel. In contrast, all previously designed SQKD protocols rely on two-way quantum communication. Security analyses prove that the presented protocols are secure against various well-known attacks and highly efficient. The utilization of the presented protocols in wireless sensor communications opens up new avenues for secure and trustworthy data transmission, enabling the deployment of resilient WSNs in critical applications. This work also paves the way for future exploration of quantum-based security protocols and their integration into WSNs for enhanced data protection.

Applications, Restrictions, and Evaluation of Quantum Cryptography for Secure Unmanned Aerial Vehicle Communication

Because of the abrupt increase in demand for security, researchers have developed immediate safety solutions that outperform state-of-the-art solutions. Data security was first sought for during the Spartan period. These days, efforts are being made to broaden this area of study by challenging the status quo and creating novel algorithms that outperform their weaker predecessors. Unmanned aerial vehicles, or UAVs, are widely used in a variety of industries, including agriculture, the military, healthcare, monitoring and surveillance, and many more, because of their svelte designs and adaptable mobility. In this post, we go over the significance of drone technology as well as its growth and demand. The study also discusses the current state of security concerns in real-time settings and how quantum cryptography outperforms conventional methods in protecting data. This inspires us to offer an overview of quantum cryptography's significance, function, and advantages in protecting UAV communications that go beyond 5G networks. Additionally, a unique layered architectural approach based on quantum cryptography is suggested to ensure excellent data security and effective transmission. A case study on the Internet of Military Things' implementation in the battlefield is also included in this presentation. The latency, security, and dependability of the suggested case study system are taken into account while assessing its performance.

A high throughput Intrusion Detection System (IDS) to enhance the security of data transmission among research centers

Data breaches and cyberattacks represent a severe problem in higher education institutions and universities that can result in illegal access to sensitive information and data loss. To enhance the security of data transmission, Intrusion Prevention Systems (IPS, i.e., firewalls) and Intrusion Detection Systems (IDS, i.e., packet sniffers) are used to detect potential threats in the exchanged data. IPSs and IDSs are usually designed as software programs running on a server machine. However, when the speed of exchanged data is too high, this solution can become unreliable. In this case, IPSs and IDSs designed on a real hardware platform, such as ASICs and FPGAs, represent a more reliable solution. This paper presents a packet sniffer that was designed using a commercial FPGA development board. The system can support a data throughput of 10 Gbit/s with preliminary results showing that the speed of data transmission can be reliably extended to 100 Gbit/s. The designed system is highly configurable by the user and can enhance the data protection of information transmitted using the Ethernet protocol. It is particularly suited for the security of universities and research centers, where point-to-point network connections are dominant and large amount of sensitive data are shared among different hosts.

Real-time gigahertz free-space quantum key distribution within an emulated satellite overpass.

Satellite quantum key distribution (SatQKD) intermediated by a trusted satellite in a low-Earth orbit to ground stations along the satellite's path allows remote users to connect securely. To establish a secure connection, a SatQKD session must be conducted to each user over a dynamically changing free-space link, all within just a few hundred seconds. Because of the short time and large losses under which the QKD protocol will be implemented, it has not yet been possible to form a complete key by transmitting all the relevant information required within a single overpass of the satellite. Here, we demonstrate a real-time QKD system that is capable of forming a 4.58-megabit secure key between two nodes within an emulated satellite overpass. We anticipate that our system will set the stage for practical implementations of intercontinental quantum secure communications that can operate over large networks of nodes and enable the secure transmission of data globally.

Dragon fly algorithm based approach for escalating the security among the nodes in wireless sensor network based system

A new technology that is gaining popularity today is the Wireless Sensor Network. Smart sensors are being used in a variety of wireless network applications, including intruder detection, transportation, the Internet of Things, smart cities, the military, industrial, agricultural, and health monitoring, as a result of their rapid expansion. Sensor network technologies improve social advancement and life quality while having little to no negative impact on the environment or natural resources of the planet are examined in sensor networks for sustainable development. Real-world applications face challenges ensuring Quality of Service (QoS) due to dynamic network topology changes, resource constraints, and heterogeneous traffic flow. By enhancing its properties, such as maintainability, packet error ratio, reliability, scalability, availability, latency, jitter, throughput, priority, periodicity, deadline, security, and packet loss ratio, the optimized QoS may be attained. Real-world high performance is difficult to attain since sensors are spread out in a hostile environment. The performance parameters are divided into four categories: network-specific, deployment phase, layered WSN architecture, and measurability. Integrity, secrecy, safety, and security are among the privacy and security levels. This article leads emphasis on the trustworthiness of the routes as well as the nodes involved in those routes from where the data has to pass from source to destination. First of all, the nodes are deployed and cluster head selection is done by considering the total number of nodes and the distance from the base station. The proposed work uses AODV architecture for computing QoS parameters that are throughput, PDR and delay. K-means clustering algorithm is used to divide the aggregated data into three possible segments viz. good, moderate and bad as this process does not involve the labelling of aggregated data due to its supervised behavior. The proposed trust model works in two phases. In first phase, data is divided into 3 segments and labelling is done. In second phase, uses generated class objects are to be applied viz. the route records to publicize the rank of the routes followed by the rank of nodes. The proposed technique employed the statistical machine learning and swarm intelligence strategy with dragon fly algorithm in order to address the issues related effective rank generation of nodes and improving the network lifetime. Deep learning concepts can be combined with fuzzy logics approach for resolving issues like secure data transmission, trustworthiness of ranking nodes and efficient route discovery.

Multi-objective secure aware workflow scheduling algorithm in cloud computing based on hybrid optimization algorithm

Cloud computing provides the on-demand service of the user with the use of distributed physical machines, in which security has become a challenging factor while performing various tasks. Several methods were developed for the cloud computing workflow scheduling based on optimal resource allocation; still, the security consideration and efficient allocation of the workflow are challenging. Hence, this research introduces a hybrid optimization algorithm based on multi-objective workflow scheduling in the cloud computing environment. The Regressive Whale Water Tasmanian Devil Optimization (RWWTDO) is proposed for the optimal workflow scheduling based on the multi-objective fitness function with nine various factors, like Predicted energy, Quality of service (QoS), Resource utilization, Actual task running time, Bandwidth utilization, Memory capacity, Make span equivalent of the total cost, Task priority, and Trust. Besides, secure data transmission is employed using the triple data encryption standard (3DES) to acquire enhanced security for workflow scheduling. The method’s performance is evaluated using the resource utilization, predicted energy, task scheduling cost, and task scheduling time and acquired the values of 1.00000, 0.16587, 0.00041, and 0.00314, respectively.

Lightweight encryption of enterprise data and secure management of eventual graphical model construction

Abstract In this paper, we use the event map as well as the even map reaction system, combined with the lightweight network data transmission encryption method of matrix tensor product, to establish the even map model for big data security management. The transmission data is compressed and reconstructed by matrix tensor compression perception, and the lightweight AES encryption of network transmission data is encrypted using the symmetric encryption method. In the end, the effectiveness of AES encryption and decryption while transmitting plaintext data is assessed for each department of Enterprise D in the service area of Edge Server Server. The results show that the lightweight AES encryption algorithm encrypts at an average of 85.33 ms less than the AES encryption algorithm, while the decryption time is 48.17 ms less, and the operation speed is faster. The algorithm demonstrates that it ensures the security of data transmission and enhances encryption and decryption performance simultaneously. In this paper, the research realizes the enterprise data transmission encryption college transmission, which provides a reference for data encryption.

A Framework Solution for Vehicle Theft Detection by Integrating NFC With a Blockchain-Based System

Vehicle theft is a widespread and costly problem with thousands of cars stolen annually, impacting privacy, the economy, and security. Conventional database systems have proven unreliable, enabling a thriving market for stolen vehicles. In response, our study presents an innovative solution, leveraging the security of blockchain technology. By utilizing the Ethereum Virtual Machine (EVM) and Smart Contracts, our system is designed to thwart attacks, including Distributed Denial of Services (DDoS) attacks. Notably, Near Field Communication (NFC) enables the secure transmission of sensitive data for verification. Our research aims to evaluate the real-world impact of this technology, considering factors such as improvements in data security and the efficiency of the reporting process. One of the most notable outcomes of our proposal is the substantial reduction in reporting time for car theft. While conventional reporting typically takes several hours, our system streamlines the process to less than 1 minute. This innovation offers significant benefits to vehicle owners, law enforcement agencies, and the broader community.

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.

Accuracy of heart rate measured by military-grade wearable ECG monitor compared with reference and commercial monitors

IntroductionPhysiological monitoring of soldiers can indicate combat readiness and performance. Despite demonstrated use of wearable devices for HR monitoring, commercial options lack desired military features. A newly developed OMNI monitor...

Video and Image Steganography

Video steganography, a technique for embedding secret information within video sequences, has gained prominence in the domain of covert communication. By exploiting the inherent redundancy and high capacity of video data, this approach enables secure data transmission without raising suspicion. This paper delves into the intricacies of AES-based video steganography, with a particular focus on the integration of the Advanced Encryption Standard (AES) algorithm. The AES algorithm, renowned for its robust encryption capabilities, serves as a cornerstone of this steganographic approach. By encrypting the secret data prior to embedding it within the video frames, an additional layer of security is introduced, safeguarding the confidentiality of the hidden information

A novel multi-level clustering mechanism using heuristic approach for secure data transmission in WSN sector with various trust computation

Several sensor nodes are used in Wireless Sensor Networks (WSNs). A multi-level clustering-based multi-trust model is introduced in WSN. The model’s main intent is to compute trust value for performing secure transmission. Initially, to verify vulnerability, the watchdog counter provides the required trust output. Further, this is intended to build a multi-level trust clustering process. Here, multi-trust is carried out by energy trust, communication trust, and data trust. Hence, multi-trust is compared with a threshold value. Once the trust value is generated, it is given for processing the cluster groups. Due to more multi-trusting, it creates multi-level clustering for security level enhancement. After the cluster group is formed, the major aspect of CH is optimally obtained with a Modified Exploration-based Pelican Optimization Algorithm (ME-POA). Finally, performance is carried out in multi-objective functions, where parameters are defined as distance, delay, energy, and multi-trust. Thus, with the determination of optimal results, the proposed multi-level clustering proves that it offers secure data transmission over WSN.

A chaotic-based watermarking scheme for ensuring integrity of a face recognition system in public large gathering scenario

Secure data transmission is critical in public video surveillance applications such as tracking missing persons in large crowd gatherings. It may help the security personnel to monitor & record the live feeds from multiple cameras. However, this live streaming could be falsified. Various cryptographic techniques have been proposed to ensure the integrity of transmitted images, but continuous attacks still pose serious challenges to ensuring the integrity and authenticity of transmitted images. This work proposes a new chaotic-based watermarking technique to ensure the integrity of the transmitted video frames, and since the frames come from multiple cameras, the scheme should be as simple as possible and as fast as possible, the simplicity manifests in designing a fragile watermarking scheme therefore, the watermark is to be embedded in the spatial domain by direct manipulation of the values of the cover’s pixels. To ensure the security of the proposed scheme, chaotic maps have been deployed to reach an acceptable level of security with minimum computational overhead. The proposed scheme is novel in design in terms of the chaotic maps used and it is tested in challenging large gathering scenario. Experimental results demonstrate that the proposed method successfully locates any falsification in the transmitted images, and the performance of the scheme evaluates different types of attacks. Our testing results in good rate tamper of detection with TPR=99.2005, TNR=99.0777 and with a good quality of imperceptibility for the watermarked image with PSNR=43.82dB, SSIM=00.9955.

An effective process of VM migration with hybrid heuristic-assisted encryption technique for secured data transmission in cloud environment

The virtualization of hardware resources like network, memory and storage are included in the core of cloud computing and are provided with the help of Virtual Machines (VM). The issues based on reliability and security reside in its acceptance in the cloud environment during the migration of VMs. VM migration highly enhanced the manageability, performance, and fault tolerance of cloud systems. Here, a set of tasks submitted by various users are arranged in the virtual cloud computing platform by using a set of VMs. Energy efficiency is effectively attained with the help of a loadbalancing strategy and it is a critical issue in the cloud environment. During the migration of VMs, providing high security is a very important task in the cloud environment. To resolve such challenges, an effective method is proposed using an optimal key-based encryption process. The main objective of this research work is to perform the VM migration and derive the multi-objective constraints with the help of hybrid heuristic improvement. The optimal VM migration is achieved by the hybrid algorithm as Improved Binary Battle Royale with Moth-flame Optimization (IBinBRMO). It can also be used to derive the multi-objective functions by some constraints like resource utilization, active servers, makespan, energy consumption, etc. After VM migration, the data transmission should take place securely between the source and destination. To secure the data, the HybridHomophorphic and Advanced Encryption Standard(HH-AES) Algorithm, where IBinBRMO optimizes the key. After optimizing the keys, the data are securely transformed along with multi-objective functions using parameters includingthe degree of modification, hiding failure rate and information preservation rate. Thus, the effectiveness is guaranteed and analyzed with other classical models. Hence, the results illustrate that the proposed work attains better performance.

High-dimensional memristive neural network and its application in commercial data encryption communication

With the development of economic globalization, demands for digital business data sharing among different subsidiary companies are constantly emerging. How to achieve secure transmission of commercial data in the Internet of Things (IoT) is a challenging task. In this paper, we propose a memristive neural network-based method for encrypted communication of commercial data. First, a high-dimensional memristive Hopfield neural network (MMHNN) model with three memristive synapses and seven neurons is proposed and its complex dynamical behaviors are deeply analyzed. The results of theoretical analysis and numerical simulations show that the proposed MMHNN can generate quasi-periodic, periodic, chaotic and hyperchaotic attractors, as well as some controllable 1-direction (1D), 2D, 3D hyperchaotic multi-scroll attractors and other types of parametric regulatory dynamics and initial value regulation dynamics. In addition, an analog equivalent circuit for the MMHNN is constructed, and the circuit simulations experimental results demonstrate the correctness and feasibility of the multi-scroll attractors phenomena. Finally, a novel MMHNN-based encryption scheme for IoT commercial data images is proposed by applying hyperchaotic spatial multi-scroll attractors, and the performance analysis shows that the proposed system achieves good encryption performances, especially in terms of keyspace, information entropy, correlation and differential attacks. The hardware experiments further verify the effectiveness and superiority of the proposed commercial data encryption scheme based on the MMHNN.