Security Protocols Research Articles

A Secure Key Exchange and Authentication Scheme for Securing Communications in the Internet of Things Environment

In today’s advanced network and digital age, the Internet of Things network is experiencing a significant growing trend and, due to its wide range of services and network coverage, has been able to take a special place in today’s technology era. Among the applications that can be mentioned for this network are the field of electronic health, smart residential complexes, and a wide level of connections that have connected the inner-city infrastructure in a complex way to make it smart. The notable and critical issue that exists in this network is the extent of the elements that make up the network and, due to this, the strong and massive data exchanges at the network level. With the increasing deployment of the Internet of Things, a wide range of challenges arise, especially in the discussion of establishing network security. Regarding security concerns, ensuring the confidentiality of the data being exchanged in the network, maintaining the privacy of the network nodes, protecting the identity of the network nodes, and finally implementing the security policies required to deal with a wide range of network cyber threats are of great importance. A fundamental element in the security of IoT networks is the authentication process, wherein nodes are required to validate each other’s identities to ensure the establishment of secure communication channels. Through the enforcement of security prerequisites, in this study, we suggested a security protocol focused on reinforcing security characteristics and safeguarding IoT nodes. By utilizing the security features provided by Elliptic Curve Cryptography (ECC) and employing the Elliptic Curve Diffie–Hellman (ECDH) key-exchange mechanism, we designed a protocol for authenticating nodes and establishing encryption keys for every communication session within the Internet of Things. To substantiate the effectiveness and resilience of our proposed protocol in withstanding attacks and network vulnerabilities, we conducted evaluations utilizing both formal and informal means. Furthermore, our results demonstrate that the protocol is characterized by low computational and communication demands, which makes it especially well-suited for IoT nodes operating under resource constraints.

API management and cloud integration model for SMEs

In the rapidly evolving technological landscape, Small and Medium-sized Enterprises (SMEs) face significant challenges in maintaining efficient and scalable IT systems. This review outlines a strategic model for API management and cloud integration designed to enhance system performance and optimize cloud-native features. The proposed model focuses on the redesign and optimization of Application Programming Interfaces (APIs) to leverage cloud capabilities effectively, addressing common issues faced by SMEs in system integration and performance. The model begins with a comprehensive assessment of existing API architectures to identify inefficiencies and performance bottlenecks. It emphasizes the need for a cloud-native approach, which includes the adoption of microservices architecture and serverless computing. By redesigning APIs to align with cloud-native principles, the model aims to achieve greater scalability, flexibility, and responsiveness in handling varying workloads. Key components of the model include API versioning strategies, improved security protocols, and enhanced data management practices. The integration of cloud-native features such as containerization, orchestration, and automated scaling ensures that APIs are optimized for performance and reliability. This approach not only streamlines system operations but also reduces the overhead associated with traditional server-based architectures. Furthermore, the model incorporates best practices for continuous integration and continuous deployment (CI/CD), facilitating seamless updates and maintenance of APIs. It also includes monitoring and analytics tools to provide real-time insights into API performance and user interactions, enabling proactive management and optimization. By implementing this strategic model, SMEs can achieve significant improvements in system performance, reduce latency, and enhance overall cloud integration. The model supports the efficient utilization of cloud resources, leading to cost savings and improved operational efficiency. This approach positions SMEs to better compete in the digital economy by leveraging advanced technologies and optimizing their IT infrastructure.

Analysis of the Influence of Rock Mechanics Variables on the Stability of Tunnel Surrounding Rock Based on Engineering Mathematics Applications

Tunnels are essential infrastructure elements, and it is critical to maintain their stability for both operation and safety. Using engineering techniques, this study examines the correlation between rock mass motorized characteristics and tunnel surrounding rock stability. This study utilizes the multi-sensor monitoring data of the surrounding rock mechanical characteristics and tunnel support structure collected during tunnel boring machine construction as its research object. The integrated cuckoo search optimized Upgraded dynamic convolutional neural network (ICSO-UDCNN) has been utilized for predicting the tunnel parameters. In general, the surrounding rock’s hardness correlates with its level, which in turn determines how quickly tunnels are being excavated. There is a stronger correlation of 98\% between the field penetration index (FPI) variables of the rock’s characteristic slope along the conditions surrounding the tunnel. The most significant factor influencing its deformation is the surrounding rock’s mechanical characteristics. For engineers and other decision-makers engaged in tunnel design, building, and maintenance, the study’s findings add a greater understanding of the variables affecting tunnel stability. This research provides an establishment for enhancing security protocols, lowering hazards related to tunneling operation, and optimizing tunnel engineering techniques by quantitatively evaluating the influence of rock mass mechanical factors on solidity.

VANETs’ research overview updated: past, present and future

The automotive industry has been undergoing significant changes, from electric and autonomous cars to the implementation of technologies for efficient and safe communication between vehicles. Vehicular Ad Hoc Networks (VANETs), in synergy with the Internet of Things and Artificial Intelligence technologies, contribute to increasing the safety and efficiency of land transport systems, aiding in the reduction of environmental pollution, and providing multiple applications to users. This article offers a historical perspective of research in VANETs, analyzing about 600 articles published between 2007 and 2021 in important conferences and journals. A systematic methodology was adopted for the selection and analysis of the articles, focusing on criteria such as thematic relevance, research methodologies employed, and significant contributions to the field. The most promising areas, main tools, and methodologies used in the studies were identified. We detected trends in the topics addressed and their future perspectives. Additionally, a detailed discussion on the main research problems found and a comparison with other studies were carried out, highlighting gaps and persistent methodological flaws in research. Specific issues, such as the lack of standardization in simulation methodologies and the need for more realistic approaches, are emphasized. Finally, perspectives for future research in VANETs are explored, suggesting promising directions, such as the development of enhanced security protocols, integration with emerging cloud computing technologies, and exploration of new applications in smart urban scenarios.

Vulnerability module in the multi-level ontology of risk assessment of Wireless Sensor Networks

This work presents the development of a vulnerability module within a multi-level ontology for risk assessment in wireless sensor networks (WSNs) used in industrial environments. WSNs consist of multiple sensor nodes with microcontrollers, sensors, communication devices, and power sources, playing a key role in monitoring, diagnostics, and managing industrial processes. Their main advantages include reduced costs due to the lack of cabling and ease of scaling by adding new nodes. However, WSNs face significant challenges, including limited power supply, vulnerability to electromagnetic interference, low bandwidth, and exposure to cyber-attacks. These issues make them less suitable for real-time systems where fast and reliable data transmission is critical. The vulnerability module developed in this study addresses these challenges by identifying weaknesses, analyzing potential threats, and assessing risks using logical rules. These rules assess various network components such as devices, communication protocols, and external factors like physical access and radio interference. The module continuously monitors the network, detects new vulnerabilities, and provides real-time feedback to the risk assessment module, suggesting measures to mitigate risks. This enhances the security and reliability of WSNs in industrial applications. In conclusion, the vulnerability module within the multi-level ontology provides a structured approach to identifying and mitigating risks in WSNs. Despite the inherent vulnerabilities of WSNs, advancements in security protocols and energy efficiency make them increasingly viable for industrial automation and optimization.

DEAC-IoT: Design of lightweight authenticated key agreement protocol for Intra and Inter-IoT device communication using ECC with FPGA implementation

The growing reliance on wireless communication in Internet-of-Things (IoT) devices highlights the critical need for secure and efficient communication protocols, especially in environments vulnerable to cyber threats. Existing IoT protocols often lack sufficient security, creating a need for robust authentication and key exchange mechanisms that can resist attacks while maintaining low computational overhead. In this paper, we propose a fog-enabled network architecture integrated with IoT devices (Intra and Inter IoT device) and develop the DEAC-IoT scheme using Elliptic Curve Cryptography (ECC) for secure authentication and key agreement. Our protocol is designed to protect device-to-device communication from security threats in resource-constrained IoT environments. We validate DEAC-IoT’s security through both informal analysis and formal verification using the Real-Or-Random (RoR) model, demonstrating its resistance to major attacks. Simulation via the Scyther tool confirms that private parameters remain secure throughout the protocol’s execution. For practical feasibility, we implement DEAC-IoT on a Field Programmable Gate Array (FPGA) and conduct performance evaluations. The results show that our protocol surpasses existing protocols in both computational and communication efficiency, making it highly suitable for real-world IoT applications.

Rivest-Shamir-Adleman Algorithm Optimized to Protect IoT Devices from Specific Attacks

IoT devices are crucial in this modern world in many ways, as they provide support for environmental sensing, automation, and responsible resource conservation. The immense presence of IoT devices in everyday life is inevitable in the smart world. The predominant usage of IoT devices lurks the prying eyes of intentional hackers. Though there are several precautionary security systems and protocols available for generic wireless networks, it is observed that there is a need to formulate a state-of-the-art security mechanism exclusively for IoT network environments. This work is submitted here for the betterment of IoT network security. Three dedicated contributions are integrated in this work to achieve higher security scores in IoT network environments. Fast Fuzzy Anomaly Detector, Legacy Naïve Bayes Attack Classifiers, and Variable Security Schemer of Rivest-Shamir-Adleman algorithm are the novel modules introduced in this work abbreviated as ASORI. Captivating the advantages of the onboard IoT certification mechanism and selecting a dynamic security strategy are the novelties introduced in this work. ASORI model is tested with industrial standard network simulator OPNET to ensure the improved security along with vital network performance parameter betterments.

A robust algorithm for authenticated health data access via blockchain and cloud computing.

In modern healthcare, providers increasingly use cloud services to store and share electronic medical records. However, traditional cloud hosting, which depends on intermediaries, poses risks to privacy and security, including inadequate control over access, data auditing, and tracking data origins. Additionally, current schemes face significant limitations such as scalability concerns, high computational overhead, practical implementation challenges, and issues with interoperability and data standardization. Unauthorized data access by cloud providers further exacerbates these concerns. Blockchain technology, known for its secure and decentralized nature, offers a solution by enabling secure data auditing in sharing systems. This research integrates blockchain into healthcare for efficient record management. We proposed a blockchain-based method for secure EHR management and integrated Ciphertext-Policy Attribute-Based Encryption (CP-ABE) for fine-grained access control. The proposed algorithm combines blockchain and smart contracts with a cloud-based healthcare Service Management System (SMS) to ensure secure and accessible EHRs. Smart contracts automate key management, encryption, and decryption processes, enhancing data security and integrity. The blockchain ledger authenticates data transactions, while the cloud provides scalability. The SMS manages access requests, enhancing resource allocation and response times. A dual authentication system confirms patient keys before granting data access, with failed attempts leading to access revocation and incident logging. Our analyses show that this algorithm significantly improves the security and efficiency of health data exchanges. By combining blockchain's decentralized structure with the cloud's scalability, this approach significantly improves EHR security protocols in modern healthcare setting.

Open AI and its Impact on Fraud Detection in Financial Industry

As per the Nilson report, fraudulent activities targeting cards amounted to a loss of $32.34 billion globally in 2021, a 14 % increase from the previous year. Such practices can be combated by harnessing OpenAI’s powerful machine learning and automation capabilities. Such advanced technologies help financial companies avoid any potential fraud and protect their esteemed clients' interests. Through the adoption and utilization of such innovative technologies., financial institutions will be better placed to protect their customers and entities from financial losses. Digital fraudsters are skilful in identifying loopholes and have developed cunning techniques like phishing for unsuspecting victims and wittingly swindling money off them. They are also updated in using OpenAI to develop deceitful information to scam people. This has seen the emergence of names like WormGPT and FraudGPT, reliant on generative AI models used by tech corporations with fraud intents. As a result, fraud detection techniques have to evolve with time as fraudsters progressively devise new techniques that bypass old and rigid banking security protocols and learn how to convince unsuspecting individuals to dispatch their money to them.

Integration of Cybersecurity, Usability, and Human-Computer Interaction for Securing Energy Management Systems

The energy sector is a critical contributor to the growth and development of any country’s economy. However, ensuring robust cybersecurity within the context of smart energy services presents persistent usability challenges in an increasingly digital environment. This study explores the intersection of human-computer interaction (HCI), cybersecurity, and usability to identify and address issues that impact the overall security of smart energy management systems. By analyzing the complex relationships between users and security protocols, this research aims to enhance the security framework, promote better user adherence, and improve system usability. The study focuses on three primary objectives: (1) identifying the most prevalent usability issues in current cybersecurity practices; (2) examining the relationship between HCI and user compliance with security measures; and (3) proposing strategies to improve cybersecurity usability by leveraging HCI principles. Hybrid approaches utilizing artificial intelligence facilitate empirical analysis and framework evaluation. Additionally, a comparative study with six existing models has been conducted. By envisioning a future where security measures not only ensure enhanced protection but also integrate seamlessly into user experiences, this approach seeks to provide valuable insights into ongoing cybersecurity discussions and contribute to a more resilient security landscape against evolving digital threats.

Distributed information-theoretical secure protocols for quantum key distribution networks against malicious nodes

Quantum key distribution (QKD) networks are expected to enable information-theoretical secure (ITS) communication over a large-scale network. Most research on relay-based QKD networks assumes all relays or nodes are completely trustworthy. However, this assumption is unreasonable because the malicious behavior of even a single node can undermine the security of the entire network. Currently, there is no method to directly distinguish between honest nodes and malicious nodes. Moreover, the status of nodes as honest or malicious can be dynamic. Therefore, a solution is needed that can withstand a certain proportion of malicious nodes in QKD networks. We propose a novel paradigm, inspired by distributed systems, to address the active and passive attacks by collaborating with malicious nodes in QKD networks. First, regarding security, we propose the ITS distributed authentication scheme, which additionally ensures two crucial security properties to QKD networks: identity unforgeability and non-repudiation. Second, concerning correctness, we propose an ITS fault-tolerant consensus scheme based on our ITS distributed authentication to ensure global consistency. This enables participating nodes to collaborate correctly and complete end-to-end key distribution within a constant number of communication rounds. Through our simulation, we have shown that our scheme exhibits a significantly lower growth trend in key consumption compared to the original end-to-end pre-shared keys scheme. For instance, in larger networks, such as when the number of nodes is 80, our scheme’s key consumption is only 13.1% of the pre-shared keys scheme.

Security protocol for securing notifications about dangerous events in the agglomeration

Our everyday lives cannot function without intelligent devices, which create the so-called Internet of Things networks. Internet of Things devices have various sensors and software to manage the work environment and perform specific tasks without human intervention. Internet of Things networks require appropriate security at various levels of their operation. In this article, we present a new security protocol that protects communication in IoT networks and enables interconnected devices to communicate and exchange information to increase the security of people living in urban agglomerations. The Control Station device evaluates the collected data about events that may threaten the life or health of residents and then notifies the Emergency Notification Center about it. The protocol guarantees the security of devices and transmitted data. We verified this using automatic verification technology, formal verification using Burrows, Abadi and Needham logic and informal analysis. The proposed protocol ensures mutual authentication, anonymity and revocation. Also, it is resistant to Man-in-the-middle, modification, replay and impersonation attacks. Compared to other protocols, our solution uses simple cryptographic techniques that are lightweight, stable and do not cause problems related to high communication costs. It does not require specialist equipment, so we can implement it using typical hardware. At each stage of protocol execution, communication occurs between two entities, so it does not require interaction between different entities, which may limit its adaptability in the context of interoperability.

A generalised entropic measure of steering using Tsallis entropies and the relationship with existent steering criteria

Abstract EPR steering is an asymmetric quantum correlation, as such, it is an important resource for quantum information protocols, like those used in quantum key distribution that are of tremendous relevance nowadays. The security of the aforementioned protocols can be shown by using entropic uncertainty measures, which are based on quantum information quantities, among which the entropies are found. In this work, we propose an entropic measure of steering, starting from the detection of steering given in a previous entropic uncertainty relation-based criterion, as well as using a generalised entropy, the Tsallis entropies. We define the entropic measure of steering in terms of an indicator, a quantity depending on the entropies of the measurements of the system, which assigns a value to the steering content of quantum states, while also comprising the asymmetry property of steering. We investigate the properties of the proposed quantity as a measure of steering and its asymmetry and show how it can be used for specific examples. For instance, a class of noisy two-qubit states that includes the Werner states is used to demonstrate the potential of such a proposal. Furthermore, a comparison is also made with the detection of steering in these states using existing steering criteria and the amount of steering a geometric measure for the Werner state gives.

Differential-phase-shift QKD with practical Mach–Zehnder interferometer

Abstract Differential-phase-shift (DPS) quantum key distribution stands as a promising protocol due to its simple implementation, which can be realized with a train of coherent pulses and a passive measurement unit. To implement the DPS protocol, it is crucial to establish security proofs incorporating practical imperfections in users’ devices, however, existing security proofs make unrealistic assumptions on the measurement unit using a Mach–Zehnder interferometer. In this paper, we enhance the implementation security of the DPS protocol by incorporating a major imperfection in the measurement unit. Specifically, our proof enables us to use practical beam splitters with a known range of the transmittance rather than the one with exactly 50%, as was assumed in the existing security proofs. Our numerical simulations demonstrate that even with fluctuations of ± 0.5 % in the transmittance from the ideal value, the key rate degrades only by a factor of 0.57. This result highlights the feasibility of the DPS protocol with practical measurement setups.

Enhancing user experience and trust in advanced LLM-based conversational agents

This study explores the enhancement of user experience (UX) and trust in advanced Large Language Model (LLM)-based conversational agents such as ChatGPT. The research involves a controlled experiment comparing participants using an LLM interface with those using a traditional messaging app with a human consultant. The results indicate that LLM-based agents offer higher satisfaction and lower cognitive load, demonstrating the potential for LLMs to revolutionize various applications from customer service to healthcare consultancy and shopping assistance. Despite these positive findings, the study also highlights significant concerns regarding transparency and data security. Participants expressed a need for clearer understanding of how LLMs process information and make decisions. The perceived opacity of these processes can hinder user trust, especially in sensitive applications such as healthcare. Additionally, robust data protection measures are crucial to ensure user privacy and foster trust in these systems. To address these issues, future research and development should focus on enhancing the transparency of LLM operations and strengthening data security protocols. Providing users with clear explanations of how their data is used and how decisions are made can build greater trust. Moreover, specialized applications may require tailored solutions to meet specific user expectations and regulatory requirements. In conclusion, while LLM-based conversational agents have demonstrated substantial advantages in improving user experience, addressing transparency and security concerns is essential for their broader acceptance and effective deployment. By focusing on these areas, developers can create more trustworthy and user-friendly AI systems, paving the way for their integration into diverse fields and everyday use.

Measurement Dependence can Affect Security in a Quantum Network

AbstractNetwork Nonlocality is an advanced study of quantum nonlocality that comprises network structure beyond Bell's theorem. The development of quantum networks has the potential to bring a lot of technological applications in several quantum information processing tasks. Here, the focus is on how the role of the independence of the measurement choices by the end parties in a network works and can be used to affect the security in a quantum network. In both three‐parties two‐sources bilocal network and four‐parties three‐sources star network scenarios, this study is able to show, a practical way to understand the relaxation of the assumptions to enhance a real security protocol if someone wants to breach in a network communication. Theoretically, it have been proved that by relaxing the independence of the measurement choices of only one end party, a Standard Network Nonlocality (SNN) and more stronger Full Network Nonlocality (FNN) can be created and the maximum quantum violation by the classical no‐signalling local model can be obtained. The distinguish between two types of network nonlocality, SNN and FNN, can also be made. It has been shown that FNN is a stronger correlation than SNN in the sense that the former comes in a scenario where all the sources must be nonlocal in nature.

Strategic management of diplomatic engagements, security policies, economic initiatives, and cultural influence: Analyzing Pakistan’s leadership role in South Asia's geopolitical stability

This study investigates the numerous crucial factors affecting Pakistan's strategic importance in South Asia, including economic pursuits, cultural influence, security measures, and diplomatic relations. The research uses a mixed methods approach to identify significant relationships between these traits and the perceived effectiveness of Pakistan's regional initiatives. The findings indicate that security protocols negatively impact Pakistan's strategic importance; however, they are positively influenced by economic initiatives and cultural presence in South Asia. Demographic parameters such as age and educational level strongly affect perceptions of Pakistan's regional influence. The study highlights cultural, political, and economic factors that bolster or undermine Pakistan's global stature. Policymakers seeking to enhance Pakistan's regional influence should regard these implications with gravity. The study offers valuable policy recommendations for addressing current challenges and enhances our understanding of South Asian geopolitics.

Enhancing Electronic Agriculture Data Security with a Blockchain-Based Search Method and E-Signatures

The production of digital signatures with blockchain constitutes a prerequisite for the security of electronic agriculture applications (EAA), such as the Internet of Things (IoT). To prevent irresponsibility within the blockchain, attackers regularly attempt to manipulate or intercept data stored or sent via EAA-IoT. Additionally, cybersecurity has not received much attention recently because IoT applications are still relatively new. As a result, the protection of EAAs against security threats remains insufficient. Moreover, the security protocols used in contemporary research are still insufficient to thwart a wide range of threats. For these security issues, first, this study proposes a security system to combine consortium blockchain blocks with Edwards25519 (Ed25519) signatures to stop block data tampering in the IoT. Second, the proposed study leverages an artificial bee colonizer (ABC) approach to preserve the unpredictable nature of Ed25519 signatures while identifying the optimal solution and optimizing various complex challenges. Advanced deep learning (ADL) technology is used as a model to track and evaluate objects in the optimizer system. We tested our system in terms of security measures and performance overhead. Tests conducted on the proposed system have shown that it can prevent the most destructive applications, such as obfuscation, selfish mining, block blocking, block ignoring, blind blocking, and heuristic attacks, and that our system fends off these attacks through the use of the test of the Scyther tool. Additionally, the system measures performance parameters, including a scalability of 99.56%, an entropy of 60.99 Mbps, and a network throughput rate of 200,000.0 m/s, which reflects the acceptability of the proposed system over existing security systems.

THE INTERFACE BETWEEN THE BIOCEANIC ROAD AND THE BELT AND ROAD INITIATIVE (BRI) FROM A BRAZILIAN PERSPECTIVE ON CRIMINAL ORGANIZATIONS

The current changing in world dynamics leads to an increased complexity on countries relations. From this perspective, the article's general objective analyses the impact of Latin America and East Asia integration through the Bioceanic Corridor and the Belt and Road Initiative on illicit markets. The specific objectives focus on identifying complicating elements for regional security, stemming from the collaborative and competitive engagements of actors within illegal networks. The adopted methodology is predominantly qualitative, involving bibliographic review, document analysis and case studies based on data from academic and government documents, and reports from international organizations. The addressed topics include drug and weapons trafficking, infrastructure initiatives, regional and global interconnection, and their relations to the criminal phenomena in South America. From the results obtained, the article emphasizes the anticipatory dimension, providing preventive recommendations in international collaboration, standardization of informational capabilities through common data models in road logistics hubs, and the application of security protocols in maritime hubs, with emphasis on the ARESP methodology (Risk Analysis with Emphasis on Port Security), contributing to regional integration on global security, and proposing practical and collaborative measures to anticipate and mitigate potential challenges arising from the interconnection of illicit networks on a global scale.

Enhancing vehicular NOMA communication security through reconfigurable intelligent surfaces

Physical layer security (PLS) aims to ensure the confidentiality and authenticity of transmitted data by capitalizing on the inherent randomness of wireless channels. Owing to the popularity of intelligent transportation systems (ITSs), PLS research has sparked renewed interest in the wireless research community. This paper investigates the performance of secure communication in the context of a vehicle-to-vehicle (V2V) communication scenario by employing a reconfigurable intelligent surface (RIS). Further, we introduce the concept of non-orthogonal multiple access (NOMA) to reduce latency and improve communication efficiency in V2V networks. This study aims to comprehensively analyze secrecy performance, encompassing parameters like average secrecy capacity (ASC), secrecy outage probability (SOP) and probability of non-zero secrecy capacity (PNZSC). Our research aims to highlight the efficacy of RIS in providing secure and reliable communication within V2V NOMA networks. Ultimately, our study contributes to advancing secure communication protocols in intelligent transportation systems.