Implementation Of Security Protocols Research Articles

A Practical Approach to Formal Methods: An Eclipse Integrated Development Environment (IDE) for Security Protocols

In order to develop trustworthy distributed systems, verification techniques and formal methods, including lightweight and practical approaches, have been employed to certify the design or implementation of security protocols. Lightweight formal methods offer a more accessible alternative to traditional fully formalised techniques by focusing on simplified models and tool support, making them more applicable in practical settings. The technical advantages of formal verification over manual testing are increasingly recognised in the cybersecurity community. However, applying formal methods, even in their more practical forms, outside highly specialised research settings remains challenging. For practitioners, formal modelling and verification are often too complex and unfamiliar to be used routinely. In this paper, we present an Eclipse Integrated Development Environment for the design, verification, and implementation of security protocols and evaluate its effectiveness, including feedback from users in educational settings. It offers user-friendly assistance in the formalisation process as part of a Model-Driven Development approach. This IDE centres around the Alice & Bob (AnB) notation, the AnBx Compiler and Code Generator, the OFMC model checker, and the ProVerif cryptographic protocol verifier. For the evaluation, we identify the six most prominent limiting factors for formal method adoption, based on relevant literature in this field, and we consider the IDE’s effectiveness against those criteria. Additionally, we conducted a structured survey to collect feedback from university students who have used the toolkit for their projects. The findings demonstrate that this contribution is valuable as a workflow aid and helps users grasp essential cybersecurity concepts, even for those with limited knowledge of formal methods or cryptography. Crucially, users reported that the IDE has been an important component to complete their projects and that they would use again in the future, given the opportunity.

Implementing Enterprise-Scale iOS MDM : A Technical Deep Dive

As organizations increasingly adopt mobile technologies, the need for effective remote management of iOS devices has grown significantly. This technical article examines implementation strategies and real-world performance metrics from a study of Mobile Device Management (MDM) implementations across 12 diverse organizations, encompassing 2,500 enterprise devices during 2023-2024. The article reveals that optimized MDM solutions can achieve 99.99% uptime while reducing infrastructure costs by up to 45%. Key findings demonstrate that effective MDM implementation reduces device management costs by 64%, improves security compliance rates to 99.3%, and decreases incident response time by 73%. Through automated troubleshooting and optimization, organizations experienced a 67% reduction in security incidents and a 42% decrease in IT support overhead while achieving 85% reduction in deployment time and 82% acceleration in app deployment processes. The article comprehensively evaluates architecture design, deployment metrics, security implementation, performance analysis, and scalability considerations. Implementation of advanced security protocols resulted in a 98.7% prevention rate for common mobile security threats, while maintaining 99.99% system reliability. The article also highlights the importance of phased deployment strategies, which demonstrate 43% higher success rates compared to direct full-scale implementations, and provides strategic insights for future planning and infrastructure optimization.

Seamless Transition to Post-Quantum TLS 1.3: A Hybrid Approach Using Identity-Based Encryption.

We propose a novel solution to streamline the migration of existing Transport Layer Security (TLS) protocol implementations to a post-quantum Key Encapsulation Mechanism for Transport Layer Security (KEMTLS). By leveraging Identity-Based Encryption (IBE), our solution minimizes the necessary modifications to the surrounding infrastructure, enabling the reuse of existing keys and certificates. We provide a proof-of-concept implementation and performance analysis, demonstrating the practical feasibility and effectiveness of our proposed approach.

Integrating IoT and Machine Learning for Advanced Breast Cancer Detection: A Secure Framework for Enhanced Diagnostic Accuracy

Background: Breast cancer continues to be a major global health issue, with outmoded analytic methods often limited in their capacity for early detection. The emergence of telehealth care emphasizes the need for advanced, advanced diagnostic explanations. Objective: This study explores the possibility of integrating advanced technologies, such as thermal imaging cameras, with sophisticated ML algorithms, particularly CNNs, to enhance breast cancer discovery beyond the capabilities of conventional risk models. Method: We propose a pioneering predictive healthcare system that harnesses the IoT and EHRs for real-time, automated breast cancer detection. This system is designed to operate in various healthcare environments, including hospitals, nursing homes, and schools. Beyond early breast cancer detection, it seeks to identify other health issues using the shared rule of DL and IoT techniques. To maintain data integrity and protect patient confidentiality, the system implements strong security protocols, including encrypted data transmission, secure access controls, and adherence to healthcare data protection regulations. Results: The study explores the methodologies and technological frameworks necessary for developing this comprehensive cancer detection system. Emphasis is placed on secure data management practices and the implementation of security protocols to safeguard sensitive health information. Main Findings: This research assesses whether the proposed system can effectively address global challenges related to breast cancer detection and contribute to enhanced patient outcomes. The integration of advanced security features aims to defend patient data and certify the system's reliability and trustworthiness in diverse healthcare settings. Conclusion: This investigate evaluates capabilities of new health care system that combines smart technologies with ML methods to identify breast cancer and possibly other health problems at an early stage. Future investigate should focus on assessing the system’s practical feasibility and effectiveness in real-world scenarios, as well as its ability to uphold stringent security standards. This emphasizes its efficiency when operating on a lightweight and portable processor. Our experimental results indicate that our system achieves a 96.32% accuracy on the BreakHis database and can operate on a Raspberry Pi device with minimal resources.

New Technology in Marine Logistics Warehouse Management

The marine logistics industry faces challenges in improving efficiency, reducing operational costs, and supporting environmental sustainability. One crucial aspect that can be optimized is warehouse management, which is responsible for the storage, handling, and distribution of cargo. This research aims to explore the application of new technologies such as the Internet of Things (IoT), artificial intelligence (AI), robotics, automation, and green technologies in marine logisticswarehousemanagement. Themethodology used includes a comprehensive literature review, in-depth interviews with industry experts, and analysis of case studies of new technology implementation in marine logistics companies. The results revealed significant opportunities and benefits from the implementation of new technologies, such as improved visibility and real-time monitoring of cargo, optimization of cargo storage and handling, increased productivity and safety, and reduced operational carbon footprint. However, challenges such as initial investment costs, data security, system interoperability, and human resource training needs must be overcome. This research presents a comprehensive implementation strategy, including cost-benefit analysis, development of industry standards, implementation of strict security protocols, and collaboration between industry, government, and standardization bodies.A conceptual framework is developed to provide practical guidance for the marine logistics industry to effectively implement new technologies and optimize their benefits. By adopting new technologies appropriately, the marine logistics industry can improve its competitiveness and global supply chain performance, and support environmental sustainability.

Towards a quantum-safe 5G: Quantum Key Distribution in core networks

The Service-Based Architecture (SBA) of the fifth generation (5G) of cellular networks introduced great advancements in flexibility, efficiency, and performance of modern networks, thanks to the distribution and softwarization of core network entities called Network Functions (NFs). Due to the distributed nature of 5G systems, these NFs are usually located in different sites to provide better Quality of Service (QoS) or specific services, which poses a great challenge regarding security. However, even though the 3GPP standard identifies security requirements by leveraging Transport Layer Security (TLS) authentication and OAuth2.0 authorization, current experimental and commercial deployments often disregard these aspects for the sake of simplicity and performance. In fact, even though data and communication protection is crucial, the implementation of security protocols and mechanisms complicates the deployments and may reduce the efficiency of 5G systems. This paper presents a novel solution that implements TLS for authentication and encryption leveraging entanglement-based Quantum Key Distribution (QKD), ensuring that all the communications between NFs in the 5G core network are secured by QKD keys, and are therefore quantum-safe. Additionally, this paper presents a QKD key repository using the Network Repository Function (NRF), which stores and relays TLS session keys to authenticated consumer NFs to access producer NFs in a fast but quantum-safe process. The solution was validated in a real hardware environment, and obtained results demonstrate that the proposed solution enhances the security of the SBA communications in an efficient way, reducing an 85% the service request time compared to the traditional TLS-based procedure, as well as 29.96% fewer bytes transmitted throughout the process.

Quantum Deep Neural Network Based Classification of Attack Vectors on the Ethereum Blockchain

INTRODUCTION: The implementation of robust security protocols is imperative in light of the exponential growth of blockchain-based platforms such as Ethereum. The importance of developing more effective strategies to detect and counter potential attacks is growing in tandem with the sophistication of the methods employed by attackers. In this study, we present a novel approach that leverages quantum computing to identify and predict attack vectors on the Ethereum blockchain. OBJECTIVES: The primary objective of this study is to suggest an innovative methodology for enhancing the security of Ethereum by leveraging quantum computing. The purpose of this study is to demonstrate that QRBM and QDN are efficient in identifying and predicting security flaws in blockchain transactions. METHODS: We combined methods from quantum computing with social network research approaches. An enormous dataset containing both genuine Ethereum transactions and a carefully chosen spectrum of malicious activity indicative of popular attack vectors was used to train our model, the QRBM. Thanks to the dataset, the QRBM was able to learn to distinguish between typical and out-of-the-ordinary activities. RESULTS: In comparison to more conventional deep learning models, the QRBM showed substantially better accuracy when it came to identifying transaction behaviours. The model's improved scalability and efficiency were made possible by its quantum nature, which is defined by features like entanglement and superposition. Specifically, the QRBM handled non-informative inputs better and solved problems faster. CONCLUSION: This study paves the way for further investigation into quantum-enhanced cybersecurity measures and highlights the promise of quantum neural networks in strengthening the security of blockchain technology. According to our research, quantum computing has the potential to be an essential tool in creating Ethereum-style blockchain security systems that are more advanced, efficient, and resilient.

SECURING CYBERSPACE AGAINST CYBERBULLYING: A WIRELESS NETWORK SECURITY PERSPECTIVE

Cyberbullying has emerged as a pervasive issue in today''''''''s digitally connected society, with detrimental effects on individuals’ mental health and well-being. Despite increasing awareness and efforts to address cyberbullying, there remains a significant gap in utilizing wireless network security measures as a means of mitigation. The existing literature predominantly focuses on social and psychological aspects of cyberbullying, overlooking the potential role of wireless network security in prevention and intervention strategies. This research seeks to fill this gap by exploring the effectiveness of leveraging wireless network security to secure cyberspace against cyberbullying incidents. The research employs a multifaceted methodology, beginning with the estimation of expected rates and derivative risks of cyberbullying within wireless networks. These metrics are combined into a risk index value, which serves as a basis for prioritizing mitigation efforts. Additionally, the study explores the application of cyberspace modeling techniques, specifically Support Vector Machines (SVM), to enhance screening processes and identify potential cyberbullying incidents on Wireless Network Security (WNS). The findings of this research demonstrate the efficacy of integrating wireless network security measures into cyberbullying prevention strategies. By combining risk index values and leveraging SVM-based cyberspace modeling, the study identifies and prioritizes cyberbullying risks effectively. Furthermore, the implementation of wireless network security protocols contributes to a reduction in cyberbullying incidents, fostering safer digital environments for users.

A comprehensive examination of security and privacy in precision agriculture technologies

Precision agriculture has revolutionized modern farming practices by integrating cutting-edge technologies such as sensors, drones, and data analytics to optimize crop management. While these advancements offer unprecedented benefits in terms of yield optimization and resource efficiency, they also raise significant concerns regarding the security and privacy of sensitive agricultural data. This research paper delves into the intricate landscape of precision agriculture security and privacy, aiming to identify potential threats, vulnerabilities, and the corresponding measures necessary for safeguarding farmers' data and ensuring the sustainability of precision farming practices. The study employs a multidisciplinary approach, combining insights from computer science, agriculture, and privacy studies to provide a comprehensive overview. Through an analysis of existing security frameworks and privacy regulations, this paper proposes recommendations for the development and implementation of robust security protocols and privacy-enhancing technologies tailored to the unique challenges of precision agriculture. The findings of this research contribute to the ongoing dialogue on responsible technology adoption in agriculture, emphasizing the importance of striking a balance between innovation and the protection of farmers' sensitive information in the era of precision farming.

RANCANG BANGUN APLIKASI PENGARSIPAN DOKUMEN DALAM PENGELOLAAN DAN PENCARIAN PADA KANTOR PELAYANAN PAJAK PRATAMA PRABUMULIH

This research aims to design and develop a document archiving application that can assist tax officials in managing and retrieving document archives at the Pratama Tax Service Office in Prabumulih. This application is designed to streamline the document archiving process for tax officials by providing features such as input for incoming archives, outgoing archives, as well as reports on incoming and outgoing archives. Additionally, this application also ensures data security through the implementation of security protocols and data encryption. The research employs the waterfall method for designing and constructing this application, encompassing stages of requirement analysis, design, coding, and testing. The outcomes of this research are expected to enable this application to assist tax officials in effectively and efficiently managing document archives. Furthermore, it is anticipated that this application will help alleviate difficulties and inconveniences in financial reporting processes and enhance the quality of document archiving reports at the Pratama Tax Service Office in Prabumulih.
 
 Keywords: Application, Archiving, Archive Reporting.

The Development of a Secure Internet Protocol (IP) Network Based on Asterisk Private Branch Exchange (PBX)

The research problem described in this article is related to the security of an IP network that is set up between two cities using hosting. The network is used for transmitting telephone traffic between servers located in Germany and the Netherlands. The concern is that with the increasing adoption of IP telephony worldwide, the network might be vulnerable to hacking and unauthorized access, posing a threat to the privacy and security of the transmitted information. This article proposes a solution to address the security concerns of the IP network. After conducting an experiment and establishing a connection between the two servers using the WireShark sniffer, a dump of real traffic between the servers was obtained. Upon analysis, a vulnerability in the network was identified, which could potentially be exploited by malicious actors. To enhance the security of the network, this article suggests the implementation of the Transport Layer Security (TLS) protocol. TLS is a cryptographic protocol that provides secure communication over a computer network, ensuring data confidentiality and integrity during transmission. Integrating TLS into the network infrastructure, will protect the telephone traffic and prevent unauthorized access and eavesdropping.

Machine and Deep Learning for IoT Security and Privacy: Applications, Challenges, and Future Directions

The integration of the Internet of Things (IoT) connects a number of intelligent devices with minimum human interference that can interact with one another. IoT is rapidly emerging in the areas of computer science. However, new security problems are posed by the cross-cutting design of the multidisciplinary elements and IoT systems involved in deploying such schemes. Ineffective is the implementation of security protocols, i.e., authentication, encryption, application security, and access network for IoT systems and their essential weaknesses in security. Current security approaches can also be improved to protect the IoT environment effectively. In recent years, deep learning (DL)/machine learning (ML) has progressed significantly in various critical implementations. Therefore, DL/ML methods are essential to turn IoT system protection from simply enabling safe contact between IoT systems to intelligence systems in security. This review aims to include an extensive analysis of ML systems and state-of-the-art developments in DL methods to improve enhanced IoT device protection methods. On the other hand, various new insights in machine and deep learning for IoT securities illustrate how it could help future research. IoT protection risks relating to emerging or essential threats are identified, as well as future IoT device attacks and possible threats associated with each surface. We then carefully analyze DL and ML IoT protection approaches and present each approach’s benefits, possibilities, and weaknesses. This review discusses a number of potential challenges and limitations. The future works, recommendations, and suggestions of DL/ML in IoT security are also included.

Innovation, transport security and supply chains: a review

ABSTRACT The recent decades have witnessed a progressive increase of global supply chains that have been related to most produced goods. Within this phenomenon, transport security has gained more and more importance, also because of the threats coming from organised crime and international terrorist groups. In this context, many stimuli have fostered investments on innovative technologies involving all transport modes. Some innovations are mode-specific while others are common to all of them, as in the case of cyber-security. On the basis of a thorough review of the literature, the main aim of the paper is to consider the impact of transport security innovations on supply chains, especially in terms of time and of economic costs. It emerges that momentous consequences can be generated by a security breach for all the firms and regions whose economic activities are reliant on the supply chain. The main implications of the analysis are that it is then necessary a coordination and collaboration among several private and public stakeholders, not only at the local and national level, but also at the supranational level. Moreover, the trade-off which may exist between the implementation of stricter security protocols and the impact on the speed and on the cost of supply chain activities must be taken into account.

COVID-19 Safety and Preventive Measures and Social Norms: How It Shaped Airlines Passengers’ Trustworthiness

In the era of COVID-19, travel decisions are influenced by social norms, which is a deciding factor between one’s perception of risk and their travel intention. Moreover, serious safety measures, such as increased aircraft cleaning, social distancing during the boarding process, and the use of face masks are critical factors that influence passengers’ trust in air travel. This study examines the direct effects of safety and preventive measures and social norms on passengers’ trust in travelling with airlines. A total of 210 responses were obtained online. Multiple regression analysis was used to test the study hypotheses. Based on the result, social norms are the most influential predictors of passengers’ trust, followed by safety and preventive measures. Furthermore, the study suggests that media coverage and social circle influence can be critical elements in transferring information to passengers, influencing their decision, and instill trust to travel during the pandemic. Notably, apart from exercising social norms, the airline industry also needs to focus on safety and preventive measures consisting of staff safety practices towards the passenger and new standard operating procedures (SOPs) during the COVID-19 pandemic. The study findings assist the airline industry in understanding passengers’ post-pandemic travelling behaviour. Notably, the implementation of health security protocols at airports, supported by the provision of continuous safety information, is indeed an important feature for passengers.

Compression and Encryption of Vital Signals Using an SoC-FPGA

This article presents the implementation of a remote monitoring system of biomedical signals with cybersecurity support and compression of vital sign signals and data of the patient. This system uses a low-cost microsystem for encrypting and compressing the information using the Lempel–Ziv–Welch (LZW) lossless compression algorithm and the Advanced Encryption Standard (AES). In this case, WolfSSL library is used for the implementation of the Transport Layer Security (TLS) protocol, whose encryption function is accelerated by the AES processor designed on a System on Chip - Field Programmable Gate Array (SoC-FPGA) device. A multiparameter board and an SoC-FPGA development board make up the vital signs measurement system, which was calibrated and verified by a commercial patient simulator. Data transmission tests were carried out from the measurement system to the monitoring application developed in LabVIEW and implemented on a personal computer (PC), where vital signs and data of the patient are decrypted and decompressed. Also, it was possible to verify a significant improvement in the performance of the TLS connection. From the results obtained, it can be concluded that the designed microsystem allows to compress, encrypt, and transmit biomedical data in real-time and without loss of information. The microsystem is very suitable for e-health platforms and/or e-health devices that use unsecured communication networks with limited bandwidth.

A Formal Verification Method for Security Protocol Implementations Based on Model Learning and Tamarin

The verification of security protocol implementations is notoriously difficult and important. In this paper, combining with the model learning using Tamarin, a formal verification tool of protocol specification, a formal verification method for security protocol implementations is proposed. We extract state machine information from protocol implementations by model learning, and determine suspicious paths in the finite-state machines by cross-validation between different implementations of the same protocol; and then verify whether the suspicious paths violate the security properties of the protocol using Tamarin. It can be used to detect logical errors in protocol implementations and avoid relying on expert experience to make compliance rules from protocol documents when using model checking tools. The effectiveness of this method is demonstrated by the vulnerability detection of the typical ChangeCipherSpec in the TLS protocol implementation. The method proposed can help developers to develop more robust implementations of security protocols.

Hybrid Model of Quantum Transfer Learning to Classify Face Images with a COVID-19 Mask

The problem of the COVID-19 disease has deter-mined that about 219 million people have contracted it, of which 4.55 million died. This importance has led to the implementation of security protocols to prevent the spread of this disease. One of the main protocols is to use protective masks that properly cover the nose and mouth. The objective of this paper was to classify images of faces using protective masks of COVID-19, in the classes identified as correct mask, incorrect mask, and no mask, with a Hybrid model of Quantum Transfer Learning. To do this, the method used has made it possible to gather a data set of 660 people of both sexes (man and woman), with ages ranging from 18 to 86 years old. The classic transfer learning model chosen was ResNet-18; the variational layers of the proposed model were built with the Basic Entangler Layers template for four qubits, and the optimization of the training was carried out with the Stochastic Gradient Descent with Nesterov Momentum. The main finding was the 99.05% accuracy in classifying the correct Protective Masks using the Pennylane quantum simulator in the tests performed. The conclusion reached is that the proposed hybrid model is an excellent option to detect the correct position of the protective mask for COVID-19.

Exploration of Solar Cell Materials for Developing Novel PUFs in Cyber-Physical Systems

Internet of Things (IoT) devices can be considered a significant component within cyber-physical systems. They can provide network communication in addition to controlling the various sensors and actuators that exist within the larger cyber-physical system. IoT devices tend to be small and contain a limited battery supply. They typically have strict constraints placed on their power consumption and available hardware resources. It is for these reasons that energy-efficiency is a major consideration in the design of these resource-constrained devices. In addition, these devices are often deployed in unsecured locations which raises concerns about the security of the device. However, the limited amount of available resources presents an obstacle towards the implementation of security protocols for these cyber-physical systems. Physically Unclonable Functions (PUFs) show promise as a potential security option. PUFs can help provide protection from issues such as IC piracy, counterfeiting, etc. Furthermore, solar cells have been utilized as a power source in IoT devices. In this paper, we propose a novel solar cell-based PUF that leverages the intrinsic variations present in solar cells. As a proof of concept, we have constructed multiple copies our proposed solar cell-based PUF using amorphous silicon, monocrystalline silicon, and polycrystalline solar cells. The reliability and uniformity of the responses produced by the copies of the PUFs made from the different types of solar cells were evaluated against variations in temperature and light intensity. From our experiments, we found that with respect to temperature the range of average reliability values was 84.41–91.20% and the range of average uniformity values was 49.34–51.26%. With respect to light intensity, the range of average reliability values was 95.45–97.75% and the range of average uniformity values was 48.74–52.81%. In addition, Monte Carlo simulations performed on monocrystalline silicon resulted in a uniqueness value of 49.989%.

Anomaly-based Detection of Blackhole Attacks in WSN and MANET Utilizing Quantum-metaheuristic algorithms

Wireless sensor network (WSN) comprises various distributed nodes that are physically separated. Nodes are constantly applying for sensing their environment. If the information sensitivity coefficient is very high, data should be conveyed continually and also with confidentially. WSNs have many vulnerability features because of data transferring on the open air, self-organization without reformed structure, bounded range of sources and memory, and limited computing capabilities. Therefore, the implementation of security protocols in WSN is inescapable. According to the resemblance between WSN and biotic reaction to the real menace in nature, bio-inspired approaches have variant rules in computer network investigations. In this paper, we exploited an ant colony optimization (ACO) algorithm based on Ad-hoc On-Demand Distance Vector (AODV) protocol for detection of black hole attacks. Finally, the Grover quantum metaheuristic algorithm is applied to optimize attack paths detection. The results gained from extensive simulations in WSN proved that the proposed approach is capable of improving some fundamental network parameters such as throughput, end-to-end delay, and packet delivery ratio in comparison with other approaches.

Key Distribution and Management in WSN Security: A State of the Art

Offering efficient key management scheme (KMS) in WSN faces many challenges that will significantly impact the design and implementation of security protocols for WSN. The goal of KMS is to provide an effective environment in which the sensor node can communicate in a secure manner. It should be able to resolve the issue of generate, allocate the cryptographic keys in WSN in an efficient and effective manner. Hence, the methods for trustworthy allocation and management of these keys are very important for security of WSN. Many KMSs have been developed in recent years. However inherent characteristics of a WSN make incorporating security a great challenge. This paper presents a comprehensive review of current state-of-the-art of KMS designed for WSN security and compare with respect to several evaluation metrics. This paper also investigates the security requirements, goals and challenges of KMS based on existing literature reviews. We also attempt to provide insight in to potential research trends in the area of WSN security and outline the approaches that are likely to play a very important role.