Secure Communication Research Articles

Context-Aware Prediction with Secure and Lightweight Cognitive Decision Model in Smart Cities

Cognitive networks with the integration of smart and physical devices are rapidly utilized for the development of smart cities. They are explored by many real-time applications such as smart homes, healthcare, safety systems, and other unpredictable environments to gather data and process network requests. However, due to the external conditions and inherent uncertainty of wireless systems, most of the existing approaches cannot cope with routing disturbances and timely delivery performance. Further, due to limited resources, the demand for a secure communication system raises another potential research challenge to protect sensitive data and maintain the integrity of the urban environment. This paper presents a secured decision-making model using reinforcement learning with the combination of blockchain to enhance the degree of trust and data protection. The proposed model increases the network efficiency for resource utilization and the management of communication devices with the alliance of security. It provides a reliable and more adaptive paradigm by exploring learning techniques for dealing with the intrinsic uncertainty and imprecision of cognitive systems. Also, the incorporation of blockchain technology reduces the risk of a single point of failure, malicious vulnerabilities, and data leakage, ultimately fostering trust for urban sensor applications. It validates the incoming routing links and identifies any communication fault incurred due to malicious interference. The proposed model is rigorously tested and verified using simulations and its significance has been proven for network metrics in comparison to existing solutions.

A Gray Image Quantum Encryption using GNEQR Representation

In the digital era, characterized by extensive online data exchange, information security has become a priority. While traditional encryption methods have proven effective in protecting data transfers, the advent of advanced quantum computing has increased susceptibility to security breaches. Quantum encryption provides a revolutionary solution to this problem by using quantum mechanics principles to establish algorithms that are impermeable to decryption. Using these quantum properties, cryptographic protocols are developed to provide superior security, unlike traditional encryption methods. The image plays an important role in transmitting information in all areas. Therefore, quantum image encryption methods are specifically designed to counter the potential risks posed by quantum computers, which can compromise conventional encryption protocols. This ensures the preservation of data security despite advances in quantum computing technology. In addition, quantum image encryption improves data transmission efficiency by establishing secure communication channels using quantum stats, thereby reducing the need for bandwidth and improving transmission speed. This paper proposes a new method of quantum encryption based on GNEQR representation and the modification of pixel values and positions in an image. After converting the image into a quantum form, we applied an algorithm to modify the values and positions of the pixels using a succession of quantum gates. We concluded this study with a statistical analysis showing the robustness of our quantum image encryption method.

Feistel inspired novel hybrid cryptosystem for information secure processing

In this paper, we propose a novel hybrid encryption algorithm that enhances security by integrating DNA encoding, the Rabin algorithm, a one-time pad (OTP), and a Feistel-inspired structure. The algorithm begins with the application of a DNA-based OTP key, used exclusively for a single secure communication session. In the second step, it combines public and private keys to generate a Rabin key. By incorporating a Feistel-inspired scheme and leveraging the inherent randomness of DNA sequences, the resulting ciphertext achieves a high level of security, making it significantly more challenging to decrypt without the private key.

Cybersecurity in Autonomous Systems: Protecting AI-Driven Applications

Autonomous systems, driven by advancements in AI, are transforming industries like transportation, healthcare, and manufacturing. These systems operate without constant human intervention, making them susceptible to various cyber threats. This paper addresses cybersecurity challenges specific to AI-driven autonomous systems and provides guidance on protecting these applications by focusing on secure communication, data privacy, and algorithm integrity. Effective approaches for implementing cybersecurity protocols in autonomous systems are also discussed to ensure data protection, system reliability, and compliance with evolving regulatory standards. Keywords Autonomous Systems, Cybersecurity, AI, Secure Communication, Algorithm Integrity, Data Privacy, Threat Modeling, Autonomous Vehicles, Drones, Robotics

Cryptography in IoT: Securing the Next Generation of Connected Devices

The Internet of Things (IoT) has revolutionized connectivity across diverse industries, linking billions of devices for optimized operations, data-driven insights, and enhanced consumer experiences. However, IoT's vast scale, heterogeneity, and resource-constrained devices introduce severe security challenges, with data integrity and privacy at risk. This white paper explores the application of cryptographic methods in securing IoT, addressing the unique constraints IoT presents, and highlighting recent advancements in lightweight cryptography, key management, and authentication protocols tailored to IoT requirements. Key words: IoT Security, Cryptography, Lightweight Encryption, Key Management, Authentication, Secure Communication

An Efficient Lattice‐Based Heterogeneous Signcryption Scheme for VANETs

ABSTRACTNowadays, vehicular ad‐hoc networks (VANETs) offer increased convenience to drivers and enable intelligent traffic management. However, the public wireless transmission channel in VANETs brings challenges related to security vulnerabilities and privacy leakage, in addition, vehicles produced by different manufacturers may use different cryptosystems such as certificateless cryptosystems (CLCs) and identity‐based cryptosystems (IBC). To address privacy leakage during cross‐cryptosystem communication in VANETs, we propose a lattice‐based heterogeneous signcryption scheme named LHS‐C2I. The scheme facilitates secure multi‐cryptosystem bidirectional communication as CLC‐based vehicles to IBC‐based vehicles and IBC‐based vehicles to CLC‐based vehicles. The confidentiality and authenticity of LHS‐C2I help to prevent the users from privacy leakage during cross‐cryptosystem communication and to authenticate the message integrity and the sender's identity legitimacy. The proposed scheme is proven to achieve Indistinguishability under Chosen Ciphertext Attack (IND‐CCA2) and Existential Unforgeability against Adaptive Chosen Messages Attack (EUF‐CMA) within the random oracle model. Performance analysis demonstrates that LHS‐C2I outperforms existing schemes in terms of computational overhead, communication overhead, and overall security features. It is particularly well‐suited for scenarios requiring secure communication across different cryptosystems in VANETs.

Feasibility of phase stabilization for satellite-mediated twin-field quantum key distribution

Quantum key distribution (QKD) is critical for future proofed secure communication. Satellites will be necessary to mediate QKD on a global scale. The limitations of the existing quantum memory and repeater technology mean that twin-field QKD (TF-QKD) provides the most feasible near-term solution to perform QKD with an untrusted satellite. However, the TF-QKD requires links between ground stations and satellites to be phase stable. We show that phase stabilization of the links to LEO and MEO satellites is feasible in spite of phase noise due to atmospheric turbulence, laser instability, and path length asymmetry while only incurring a quantum bit error rate (QBER) penalty of less than 1.5%. These results are also applicable to future untrusted satellite networks employing precisely synchronized quantum memories or quantum repeaters.

Intelligent two-phase dual authentication framework for Internet of Medical Things

The Internet of Medical Things (IoMT) has revolutionized healthcare by bringing real-time monitoring and data-driven treatments. Nevertheless, the security of communication between IoMT devices and servers remains a huge problem because of the inherent sensitivity of the health data and susceptibility to cyber threats. Current security solutions, including simple password-based authentication and standard Public Key Infrastructure (PKI) approaches, typically do not achieve an appropriate balance between security and low computational overhead, resulting in the possibility of performance bottlenecks and increased vulnerability to attacks. To overcome these limitations, we present an intelligent two-phase dual authentication framework that improves the security of sensor-to-server communication in IoMT environments. During the registration phase, our framework is based on Elliptic Curve Diffie-Hellman (ECDH) for rapid key exchange, and during real-time communication, our framework uses the Advanced Encryption Standard Galois Counter Mode (AES-GCM) to encrypt data securely. The efficiency of the proposed framework was rigorously tested through simulations that evaluated encryption-decryption time, computational cost, latency, and packet delivery ratio. The security resilience was also evaluated against man-in-the-middle, replay, and brute force attacks. The results show that encryption/decryption time is reduced by over 45%, overall computational cost by 45.38%, and latency by 28.42% over existing approaches. Furthermore, the framework achieved a high packet delivery ratio and strong defense against cyber threats for maintaining the confidentiality and integrity of the medical data across IoMT networks. However, the dual authentication approach doesn’t affect the functionality of medical IoT devices while enhancing IoMT security, which makes it an ideal integration option for existing healthcare systems.

RWA-BFT: Reputation-Weighted Asynchronous BFT for Large-Scale IoT

This paper introduces RWA-BFT, a reputation-weighted asynchronous Byzantine Fault Tolerance (BFT) consensus algorithm designed to address the scalability and performance challenges of blockchain systems in large-scale IoT scenarios. Traditional centralized IoT architectures often face issues such as single points of failure and insufficient reliability, while blockchain, with its decentralized and tamper-resistant properties, offers a promising solution. However, existing blockchain consensus mechanisms struggle to meet the high throughput, low latency, and scalability demands of IoT applications. To address these limitations, RWA-BFT adopts a two-layer blockchain architecture; the first layer leverages reputation-based filtering to reduce computational complexity by excluding low-reputation nodes, while the second layer employs an asynchronous consensus mechanism to ensure efficient and secure communication among high-reputation nodes, even under network delays. This dual-layer design significantly improves performance, achieving higher throughput, lower latency, and enhanced scalability, while maintaining strong fault tolerance even in the presence of a substantial proportion of malicious nodes. Experimental results demonstrate that RWA-BFT outperforms HB-BFT and PBFT algorithms, making it a scalable and secure blockchain solution for decentralized IoT applications.

On-Chip Metamaterial-Enhanced Mid-Infrared Photodetectors with Built-In Encryption Features.

The integration of mid-infrared (MIR) photodetectors with built-in encryption capabilities holds immense promise for advancing secure communications in decentralized networks and compact sensing systems. However, achieving high sensitivity, self-powered operation, and reliable performance at room temperature within a miniaturized form factor remains a formidable challenge, largely due to constraints in MIR light absorption and the intricacies of embedding encryption at the device level. Here, a novel on-chip metamaterial-enhanced, 2D tantalum nickel selenide (Ta₂NiSe₅)-based photodetector, meticulously designed with a custom-engineered plasmonic resonance microstructure to achieve self-powered photodetection in the nanoampere range is unveiled. Gold cross-shaped resonators are demonstrated that generate plasmon-induced ultrahot electrons, significantly enhancing the absorption of MIR photons with energies far below the bandgap and boosting electron thermalization in Ta₂NiSe₅, yielding a 0.1V bias responsivity of 47mA/W-an order of magnitude higher than previously reported values. Furthermore, the implementation of six reconfigurable optoelectronic logic computing ("AND", "OR", "NAND", "NOR", "XOR", and "XNOR") are illustrated via tailored optical and electrical input-output configurations, thereby establishing a platform for real-time infrared-encrypted communication. This work pioneers a new direction in secure MIR communications, advancing the development of high-performance, encryption-capable photonic systems.

Optimal Reconfigurable Intelligent Surface Deployment for Secure Communication in Cell-Free Massive Multiple-Input Multiple-Output Systems with Coverage Area

Optimal Reconfigurable Intelligent Surface Deployment for Secure Communication in Cell-Free Massive Multiple-Input Multiple-Output Systems with Coverage Area

Enhancing Data Protection and Covert Communication in Cloud Environments with Isogeny Based Cryptography and Spread Spectrum Steganography

The rise of cloud computing has changed how individuals and organizations store and communicate data, but it additionally caused significant concerns about information security and confidentiality. In order to improve data protection and allow covert communication in cloud environments, this research suggests a unique approach that combines spread spectrum steganography with isogeny-based cryptography as a solution to these problems. The main goal is to make it less difficult for two users, User 1 and User 2, to communicate private data that is kept in a cloud infrastructure through safe and covert data transfer. This technology depends on isogeny-based cryptography, which creates safe channels of communication between users by taking use of the mathematical features of isogenies of elliptic curves. Additionally, this technique provides protection from quantum assaults, consequently boosting data security. Spread Spectrum Steganography (SSIS), the second element, is used to secretly include shared secrets inside digital images. To protect secrets, SSIS encrypts, duplicates, interleaves, and employs pseudorandom noise sequences as carriers. The noise in the stegoimage is then removed with a filter to approximate the original image. By performing this, the stegoimage is made integrate in with the original, thereby hiding the secrets. Users 1 and 2 can safely share information by combining spread spectrum steganography and isogeny-based cryptography, reducing potential risks associated with parties that are unreliable. Spread spectrum steganography provides the covert hiding of transmitted secrets inside digital images, while isogeny-based cryptography provides secure communication channels. These methods are combined to build an effective structure for private and secure data sharing in cloud settings. This novel method solves important concerns about data security, secrecy, and covert communication, and thus makes a significant addition to the developing field of cloud computing security.

A New Feature Level‐Based Multi‐Biometric Identification System to Enable Secure and Reliable Communication Systems for Next‐Generation Smart Cities

ABSTRACTThe concept of smart cities, which aims to improve urban lifestyles through innovative technologies and policies, has gained significant momentum over the last few years. As we transition into the next‐generation smart city era, it is crucial to review some of the fundamental technologies driving this evolution. Among these, security‐related challenges necessitate the implementation of effective authentication systems. This paper introduces a novel feature‐based multi‐biometric identification system designed to provide secure and reliable communication frameworks for next‐generation smart cities. The use of multi‐modal biometric identification for twins has long been a fascinating and valuable area of research. Because of its high reliability and acceptance, this approach significantly advances the domain of biometric identification for twins. The unique characteristics of twins are determined by variations in features extracted during the multi‐modal biometric process. However, many of these extracted features are superfluous, expanding the search space and complicating the generalization process. Therefore, the primary challenge lies in isolating the most salient features capable of accurately identifying twins through multi‐modal biometrics. To address this challenge, this research proposes an improved twin multi‐modal biometric identification framework. The proposed method employs a fusion of Dis‐Eigen features with the SailFish optimization algorithm to enhance both accuracy and efficiency. In this study, unique biometric features of twins were extracted and simplified using the Dis‐Eigen process, after which the Sailfish algorithm was applied to optimize model parameters and improve identification accuracy. As a result, the intra‐class similarity error decreased, while the inter‐class similarity error increased, improving twin identification. Consequently, several classifier applications achieved an identification rate exceeding 93%.

Multi-IRS-Aided Secure Communication in UAV-MEC Networks

Multi-IRS-Aided Secure Communication in UAV-MEC Networks

Fixed Time Control for Interlayer Synchronism under DDMNNs and Application in Secure Communication

Fixed Time Control for Interlayer Synchronism under DDMNNs and Application in Secure Communication

آلية إدارة مفتاح RSA المحسّنة لحماية حزم التحكم في شبكات تبديل الاندفاع البصري

Optical Burst Switch (OBS) network is a typical technology currently proposed, as an infrastructure to deal with most highly demanded communication services. OBS architecture consists of Data Burst (DB) as a payload and Burst Header Packet (BHP) as a control packet. BHP carries important information about path reservation and its corresponding DB. However, the information security (Privacy, Reliability, Confidentiality, Integrity, Availability, Authentication, and Authorization) of OBS network communication has been represented as the current issues, which affect the network performance in terms of data loss and data transmission delay. This paper focuses on security weaknesses of BHP transmission in OBS network against Data Burst Redirection (DBR) Attack. The current paper was conducted to develop a protection mechanism to ensure the confidentiality and authentication of BHP. In OBS, RSA public-key encryption algorithm has been enhanced and integrated. Moreover, the Self-Controlling key distribution technique has been implemented to ensure a high security level of key transmission between each pair of OBS nodes. Three different OBS environments have been designed and implemented. These environments were established on the bases of three different concepts; OBS Topology without Security Measures and without Security Attacks, OBS Topology under Security Attacks without Security Measures, and OBS Topology under Security Attacks with Security Measures. The obtained results are based on Burst Loss Ratio, Throughputs, and Average Delay Ratio. Such a result has successfully proved the trustworthiness and efficiency of Control Packet Protection Technique (CPPT-OBS) to prevent DBR attack. Keywords: OBS , DB, BHP, DBR, RSA, CPPT

Practical Design of Probabilistic Constellation Shaping for Enhancing Performance of Physical Layer Security in Visible Light Communications

Practical Design of Probabilistic Constellation Shaping for Enhancing Performance of Physical Layer Security in Visible Light Communications

Chaos Synchronization in a Dual-Laser Chaotic Multiplexing System Based on Nanolasers

Nanolaser (NL), as an important optical source device, has a significant impact on photonic integrated circuits and has become a research hotspot in recent years. This study investigates the synchronization performance of a dual-channel laser chaotic multiplexing system based on NLs and employs an active-passive decomposition to enhance signal processing and multiplexing efficiency. By establishing a rate equation model, the synchronization characteristics of the system were analyzed, focusing on the effects of two key parameters—the Purcell factor (F) and the spontaneous emission coupling factor (β)—as well as system parameters, single-parameter mismatches, and multi-parameter mismatches. Numerical simulations show that, with proper parameter configurations, the two master NLs can maintain low correlation, ensuring the "pseudo-orthogonal" of chaotic signals while achieving high-quality chaotic synchronization with their paired slave NLs. The study found that both the Purcell factor (F) and the spontaneous emission coupling factor (β) significantly influence the synchronization performance of the system, and the optimal parameter ranges for achieving high-quality synchronization were identified. Additionally, the effects of feedback strength and frequency detuning were explored, revealing that frequency detuning plays a more critical role in the synchronization between the master NLs. The impact of parameter mismatches on system synchronization performance was also emphasized. The system exhibits robustness against single-parameter mismatches, with minimal impact on master-slave synchronization quality. However, multi-parameter mismatches introduce more complex effects. Compared to traditional semiconductor laser systems, this system can maintain "pseudo-orthogonal" over a wider parameter range, achieving higher security and lower channel interference. This research lays a theoretical foundation for chaos synchronization based on NLs and provides new insights for designing secure, stable, and efficient optical communication systems.

A conceptual approach of optimization in federated learning

Federated learning (FL) is an emerging approach to distributed learning from decentralized data, designed with privacy concerns in mind. FL has been successfully applied in several fields, such as the internet of things (IoT), human activity recognition (HAR), and natural language processing (NLP), showing remarkable results. However, the development of FL in real-world applications still faces several challenges. Recent optimizations of FL have been made to address these issues and enhance the FL settings. In this paper, we categorize the optimization of FL into five main challenges: Communication Efficiency, Heterogeneity, Privacy and Security, Scalability, and Convergence Rate. We provide an overview of various optimization frameworks for FL proposed in previous research, illustrated with concrete examples and applications based on these five optimization goals. Additionally, we propose two optional integrated conceptual frameworks (CFs) for optimizing FL by combining several optimization methods to achieve the best implementation of FL that addresses the five challenges.

A class of n-D Hamiltonian conservative chaotic systems with three-terminal memristor: Modeling, dynamical analysis, and FPGA implementation.

Memristors are commonly used to introduce various chaotic systems and can be used to enhance their chaotic characteristics. However, due to the strict construction conditions of Hamiltonian systems, there has been limited research on the development of memristive Hamiltonian conservative chaotic systems (MHCCSs). In this work, a method for constructing three-terminal memristors is proposed, and the three-terminal memristors are incorporated into the Hamiltonian system, resulting in the development of a class of n-D MHCCS. Based on this method, we model a 4D MHCCS as a standard model for detailed dynamic analysis. The dynamic analysis reveals that the MHCCS exhibits complex dynamic behaviors, including conservativeness, symmetry, chaos depending on parameters, extreme multistability, and chaos under a wide parameter range. The dynamic analysis shows that MHCCS not only retains the favorable characteristics of a conservative system but also has more complex nonlinear dynamics due to the incorporation of memristors, thereby further enhancing its chaotic characteristics. Furthermore, the pseudo-random number generator based on the MHCCS has excellent randomness in terms of the NIST test. Finally, the physical realizability of the system is verified through Field Programmable Gate Array experiments. This study demonstrates that the constructed class of MHCCSs is a good entropy source that can be applied to various chaotic embedded systems, including secure communication, cryptographic system, and pseudo-random number generator.