Secure Communication Protocol Research Articles

Multi-channel polarization manipulation based on graphene for encryption communication

Wave-based cryptography, at the vanguard of advancing technologies in advanced information science, is essential for establishing a diverse array of secure cryptographic platforms. The realization of these platforms hinges on the intelligent application of multiplexing techniques, seamlessly combined with appropriate metasurface technology. Nevertheless, existing multi-channel encryption technologies based on metasurfaces face challenges related to information leakage during partial channel decoding processes. In this paper, we present a reprogrammable metasurface for polarization modulation. This metasurface not only allows for the arbitrary customization of linearly polarized reflected waves but also enables real-time amplitude modulation. Here, relying on polarization amplitude control, a fully secure communication protocol is developed precisely in the terahertz (THz) spectrum to achieve real-time information encryption based on polarization modulation metasurfaces where access to information is highly restricted. The proposed metasurface employs the double random phase encryption (DRPE) algorithm for information encryption. It transmits the encrypted data through different polarization channels using two graphene nanoribbons, exclusively controlled by external biasing conditions. Various encryption scenarios have been outlined to fortify information protection against potential eavesdroppers. The simulated results show that this unique technology for hiding images by manipulating the polarization of the reflected wave provides new opportunities for various applications, including encryption, THz communications, THz secure data storage, and imaging.

Automated IoT Based Power Disconnection for unpaid Subscribers

This project presents an innovative solution leveraging Internet of Things (IoT) technology to automate the process of power disconnections for unpaid subscribers in utility services. The conventional method of manually disconnecting power for non-payment is not only inefficient but also poses operational challenges and risks. Our proposed system aims to address these issues by integrating IoT devices, billing systems, and automated disconnection protocols. Key features of the system include real-time monitoring of subscriber accounts, customizable disconnection thresholds, and secure communication protocols to safeguard sensitive data. Additionally, the system offers flexibility for utility providers to implement payment reminders and grace periods, enhancing customer engagement and satisfaction. Through simulations and prototype testing, we demonstrate the efficacy and reliability of our automated IoT-based power disconnection system. Our solution not only streamlines the disconnection process but also reduces operational costs, minimizes revenue losses due to non-payment, and enhances overall efficiency in utility management.

Security paradigms for IoT in telecom networks: Conceptual challenges and solution pathways

The concept paper explores the critical security challenges posed by the Internet of Things (IoT) in telecom networks and proposes solution pathways to address them. As IoT devices proliferate in telecom networks, they introduce new vulnerabilities and security threats that must be mitigated to ensure the integrity, confidentiality, and availability of network resources and data. The paper begins by highlighting the unique security challenges posed by IoT devices, including their large attack surface, resource constraints, and diverse communication protocols. These challenges are further exacerbated in telecom networks due to the scale and complexity of the infrastructure. To address these challenges, the paper proposes a multi-faceted approach that combines technical, organizational, and regulatory measures. Technical solutions include the use of secure communication protocols, device authentication mechanisms, and encryption techniques to protect data in transit and at rest. Organizational measures focus on improving security awareness and training among network operators and ensuring the secure development and deployment of IoT devices. Regulatory measures advocate for the implementation of standards and regulations that promote security and privacy in IoT deployments. The paper also discusses the importance of collaboration among stakeholders, including network operators, device manufacturers, and regulatory bodies, to address security challenges effectively. By working together, stakeholders can develop and implement best practices that enhance the security of IoT devices and telecom networks. In conclusion, the concept paper highlights the urgent need for robust security paradigms in IoT deployments within telecom networks. By implementing the proposed solution pathways and fostering collaboration among stakeholders, telecom networks can mitigate security risks and ensure the safe and secure deployment of IoT devices. Keywords: IoT, Telecom, Networks, Security.

Next-Gen Medical Technology a Smart Approach to Syringe Injection Pump Automation

This presents the design, implementation, and successful validation of a cutting-edge IoT-based Syringe Injection Pump (SIP) for precision medication administration. In response to the increasing demand for enhanced healthcare automation, this system leverages technologies to address critical challenges in medication delivery. This SIP incorporates a robust Internet of Things (IoT) framework, enabling seamless communication between the device and a central healthcare management system. The automated syringe injection process is governed by a sophisticated algorithm that considers patient-specific parameters, ensuring precise dosage administration. Through extensive testing and real-world simulations, the results demonstrate a significant reduction in human error and improved medication adherence. The system’s architecture integrates secure communication protocols, ensuring data confidentiality and integrity during transmission. An innovative user interface provides healthcare professionals with real-time monitoring and control capabilities, enhancing situational awareness and responsiveness. Furthermore, the SIP’s adaptability to diverse medical environments underscores its versatility in meeting the evolving needs of healthcare institutions. To validate the system’s effectiveness, a comprehensive performance evaluations, including dosage accuracy, response time, and reliability under varying conditions was conducted. Results indicate an impressive dosage precision of 99.8%, showcasing the system’s reliability in critical healthcare scenarios. The IoT connectivity facilitates remote monitoring and control, allowing healthcare providers to intervene promptly in case of anomalies or emergencies. In addition to its technical prowess, the SIP aligns with current healthcare trends by promoting sustainability and cost-effectiveness. The automated system optimizes resource utilization, reduces medication waste, and minimizes the environmental impact associated with traditional manual injection methods. In conclusion, this IoT-based Syringe Injection Pump represents a paradigm shift in medical technology, offering a smart and results-oriented solution for precise medication administration. The successful implementation and validation of this system pave the way for improved patient outcomes, streamlined healthcare workflows, and a more sustainable approach to medication delivery. This research contributes to the ongoing discourse on advancing medical technology and underscores the potential of IoT in shaping the future of healthcare.

Enhanced quantum secret sharing protocol for anonymous secure communication utilizing W states

Quantum secret sharing (QSS) represents the fusion of quantum mechanics principles with secret information sharing, allowing a sender to distribute a secret among receivers for collective recovery. This paper introduces the concept of quantum anonymous secret sharing (QASS) to enhance the practicality of such protocols. We propose a QASS protocol leveraging W states, ensuring both recover-security and anonymity of shared secrets. Our protocol undergoes rigorous evaluation verifying their accuracy and fortifying their security against scenarios involving the active adversary. Additionally, acknowledging the imperfections inherent in real-world communication channels, we conduct a comprehensive analysis of protocol security and efficacy in noisy quantum networks. Our investigations reveal that W states exhibit good performance in mitigating noise interference, making them apt for practical applications.

SECURITY PARADIGMS FOR IOT IN TELECOM NETWORKS: CONCEPTUAL CHALLENGES AND SOLUTION PATHWAYS

The concept paper explores the critical security challenges posed by the Internet of Things (IoT) in telecom networks and proposes solution pathways to address them. As IoT devices proliferate in telecom networks, they introduce new vulnerabilities and security threats that must be mitigated to ensure the integrity, confidentiality, and availability of network resources and data. The paper begins by highlighting the unique security challenges posed by IoT devices, including their large attack surface, resource constraints, and diverse communication protocols. These challenges are further exacerbated in telecom networks due to the scale and complexity of the infrastructure. To address these challenges, the paper proposes a multi-faceted approach that combines technical, organizational, and regulatory measures. Technical solutions include the use of secure communication protocols, device authentication mechanisms, and encryption techniques to protect data in transit and at rest. Organizational measures focus on improving security awareness and training among network operators and ensuring the secure development and deployment of IoT devices. Regulatory measures advocate for the implementation of standards and regulations that promote security and privacy in IoT deployments. The paper also discusses the importance of collaboration among stakeholders, including network operators, device manufacturers, and regulatory bodies, to address security challenges effectively. By working together, stakeholders can develop and implement best practices that enhance the security of IoT devices and telecom networks. In conclusion, the concept paper highlights the urgent need for robust security paradigms in IoT deployments within telecom networks. By implementing the proposed solution pathways and fostering collaboration among stakeholders, telecom networks can mitigate security risks and ensure the safe and secure deployment of IoT devices. Keywords: Security, IoT, Telecom, Solutions, Network.

Optimizing extreme manufacturing framework: a secure and efficient 3D printing integration framework

This study presents a comprehensive framework for extended manufacturing with integrated 3D printing technologies, exemplifying a paradigm shift in the manufacturing landscape. The Digital Thread Integration establishes a dynamic foundation, enabling real-time collaboration and data flow throughout the product lifecycle. Leveraging advanced AI-driven optimization, Digital Design Platforms streamline designs, processing 1,000 iterations per hour, and recommending materials based on component requirements. On-Demand Manufacturing Hubs strategically placed globally achieve substantial reductions in lead times (48 h) and material waste (15%). The Cybersecurity Infrastructure ensures the sanctity of the digital environment, employing secure communication protocols and an Intrusion Detection System (IDS) responding to threats in milliseconds. The Data Analytics Hub contributes to continual improvement by analysing 100 GB of 3D printing data daily, generating 50 actionable insights weekly. User Interface and Accessibility initiatives empower the workforce through intuitive training modules and responsive help desks. In conclusion, this framework exemplifies secure, efficient, and data-driven extended manufacturing, positioning the industry at the forefront of technological advancement.

Automatic Translation of English Terms for Computer Network Security Based on Deep Learning

Translation computer network security refers to the protection of sensitive information during the transmission of data across networks in different languages. With the increasing globalization of businesses and communications, the need for secure translation services has become paramount. Security measures such as encryption, authentication, and data integrity verification play a crucial role in safeguarding translations from unauthorized access, interception, or tampering. Additionally, the use of secure communication protocols and encryption algorithms ensures that data remains confidential and protected from cyber threats. This paper presents an automatic translation approach for English terms related to computer network security, leveraging deep learning techniques with Cryptographic Hashing Authentication Classification (CHAC). The proposed framework aims to enhance the accuracy and efficiency of translating security terms across different languages, facilitating effective communication and collaboration in cybersecurity contexts. Through simulated experiments and empirical validations, the effectiveness of the CHAC-enhanced deep learning model is evaluated, demonstrating significant improvements in translation accuracy and performance. For instance, the CHAC model achieved an average accuracy rate of 90% in translating security terms, outperforming traditional translation methods by 20%. Additionally, the framework reduced translation time by 30%, streamlining the process of generating multilingual security documentation and communications. These results underscore the potential of deep learning with CHAC in automating the translation of English terms for computer network security, enhancing global cybersecurity efforts and facilitating cross-cultural collaboration.

Enhancing Resilience: Smart Grid Cybersecurity and Fault Diagnosis Strategies

The increasing integration of advanced technologies within the power grid infrastructure has led to significant advancements in efficiency, reliability, and sustainability. However, this integration also introduces new vulnerabilities, particularly in the realm of cybersecurity. This paper presents an overview of smart grid cybersecurity challenges and proposes strategies for enhancing resilience through fault diagnosis techniques. Firstly, the paper examines the evolving threat landscape facing smart grids, encompassing cyber-attacks, insider threats, and natural disasters. It highlights the critical need for robust cybersecurity measures to safeguard grid operations and prevent potentially catastrophic disruptions. Next, the paper delves into various cybersecurity frameworks and standards tailored specifically for smart grids, emphasizing the importance of comprehensive risk assessment, intrusion detection systems, and secure communication protocols. Additionally, it discusses the role of machine learning and artificial intelligence in augmenting cyber defense capabilities, enabling proactive threat detection and rapid response. Furthermore, the paper explores fault diagnosis strategies aimed at maintaining grid resilience in the face of cyber incidents or physical faults. It discusses the integration of data analytics, predictive modeling, and real-time monitoring to identify and mitigate potential grid disturbances swiftly.

Secure and efficient communications with fine-grained access control in underwater wireless sensor networks

As UWSN have received attention, a need for an efficient and secure communication protocol has arisen to overcome the low device performance, node failure, and high propagation latency. However, existing works are either specialized for one-to-one communication or cannot satisfy low latency constraints. Therefore, this work proposes a secure communication protocol with fine-grained access control for UWSN that support secure and efficient one-to-many communication and considers potential internal attackers for high security level. Specifically, we adopt lightweight ABE to achieve fine-grained access control at low cost, and introduce outsourced decryption to further alleviate the computational load of underwater sensors.

Sampled-Data-Based Secure Synchronization Control for Chaotic Lur'e Systems Subject to Denial-of-Service Attacks.

This article investigates the sampled-data-based secure synchronization control problem for chaotic Lur'e systems subject to power-constrained denial-of-service (DoS) attacks, which can block data packets' transmission in communication channels. To eliminate the adverse effects, a resilient sampled data control scheme consisting of a secure controller and communication protocol is designed by considering the attack signals and periodic sampling mechanism simultaneously. Then, a novel index, i.e., the maximum anti-attack ratio, is proposed to measure the secure level. On this basis, a multi-interval-dependent functional is established for the resulting closed-loop system model. The main feature of the developed functional lies in that it can fully use the information of resilient sampling intervals and DoS attacks. In combination with the convex combination method, discrete-time Lyapunov theory, and some inequality estimate techniques, two sufficient conditions are, respectively, derived to achieve sampled-data-based secure synchronization of drive-response systems against DoS attacks. Compared with the existing Lyapunov functionals, the advantages of the proposed multi-interval-dependent functional are analyzed in detail. Finally, a synchronization example and an application to secure communication are provided to display the effectiveness and validity of the obtained results.

Security Concerns of IoT Against DDoS in 5G Systems

The Internet of Things (IoT), which enables seamless connectivity and communication between gadgets and the internet has completely changed how people interact with and use technology in 5G. Distributed Denial of Service (DDoS) assaults are now recognized as a serious security concern because of the rapid expansion of IoT devices, which has also brought about new security issues. DDoS attacks plan massive, coordinated attacks that overwhelm target systems and impair their functions by taking advantage of the interconnectedness of IoT devices. This paper explores the vulnerabilities in IoT devices and their possible exploitation by hostile actors, providing an in-depth examination of IoT and DDoS assault dynamics in 5G. The report emphasizes the need for preventative security measures by highlighting the growing size and complexity of DDoS attacks employing compromised IoT botnets. The examination of various DDoS attack channels and methodologies against IoT devices sheds light on the growing strategies used by attackers to infiltrate and manage IoT botnets. To emphasize how urgent it is to mitigate such risks, the effects of DDoS assaults on vital infrastructures, companies, and end-users are also emphasized. The paper also evaluates current mitigation techniques and security safeguards intended to counter IoT-based DDoS attacks. These include the use of security in Nexus that prioritize device authentication, encryption, and secure communication protocols as well as network traffic filtering and anomaly detection. Relevant case studies and real-world examples are provided to give readers a thorough understanding of the topic while demonstrating the scope and effects of recent IoT-based DDoS attacks. The paper guides different approaches through which DDOS can harm the server/ system (or anything, which is belonging to the family of the Internet of things) through different types; DDOS can be minimized but impossible to overcome. In this paper, we also have proved that due to IOT, the ratio of DDOS has increased by implementing these measures and continuously monitoring the network for potential threats. 5G systems can enhance their security posture and provide a safer and more reliable communication infrastructure for users and businesses by mitigating DDoS.

Enhanced Secure Communication Protocol with Pipelined Advanced Encryption for Mobile Networks

In today's increasingly connected world, the demand for secure mobile communications is paramount. The security protocols are specifically tailored for mobile communication systems, ensuring the confidentiality and integrity of sensitive data transmitted over wireless networks. It can be seamlessly integrated into various mobile applications such as messaging platforms, VoIP services, and mobile banking apps, providing end-to-end encryption for user privacy. Current encryption protocols used in mobile communications often face challenges related to performance and security. Traditional encryption methods may not adequately address the evolving threats posed by sophisticated attackers. Moreover, the computational overhead associated with encryption and decryption processes can impact the overall efficiency of mobile communication systems. This work presents a novel approach to enhancing the security of mobile communications through the design of a Pipelined Advanced Encryption Based Cryptography Protocol (PAEBCP). The proposed protocol aims to address the vulnerabilities present in existing encryption methods by leveraging a pipelined architecture for efficient encryption and decryption processes. The proposed PAEBCP protocol introduces a pipelined architecture that optimizes the encryption and decryption processes for mobile communication systems. By dividing the encryption process into multiple stages and parallelizing key operations, the protocol enhances both security and performance.

Enhancing Security in Vehicle-to-Vehicle Communication: A Comprehensive Review of Protocols and Techniques

Vehicle-to-vehicle (V2V) communication has played a pivotal role in modern intelligent transportation systems, enabling seamless information exchange among vehicles to enhance road safety, traffic efficiency, and overall driving experience. However, the secure transmission of sensitive data between vehicles remains a critical concern due to potential security threats and vulnerabilities. This research focused on investigating the security protocols that have been employed in vehicle-to-vehicle communication systems. A comprehensive review and analysis of relevant literature and research papers was conducted to gather information on existing V2V communication security protocols and techniques. The analysis encompassed key areas, including authentication mechanisms, encryption algorithms, key management protocols, and intrusion detection systems specifically applicable to V2V communication networks. Within the context of real-world V2V environments, this study delved into the challenges and limitations associated with implementing these protocols. The research aimed to provide a comprehensive understanding of the strengths and weaknesses of the current V2V communication security protocols. Furthermore, based on the findings, this paper proposes improvements and recommendations to enhance the security measures of the V2V communication protocol. Ultimately, this research contributes to the development of more secure and reliable V2V communication systems, propelling the advancement of intelligent transportation technology.

IoT Cloud Based Low-Cost Temperature, Humidity and Dust Monitoring System to Prevent Food Poisoning

This project presents a cost-effective IoT-based system designed for monitoring temperature, humidity, and dust levels in food storage environments to mitigate the risk of food poisoning. Utilizing sensors and a microcontroller, real-time data is collected and transmitted to a cloud platform through a secure communication protocol. The cloud-based solution incorporates a backend server and a database for efficient data processing and storage. A user-friendly web or mobile interface enables stakeholders to monitor conditions, set custom thresholds, and receive timely alerts. The system's design emphasizes scalability, adaptability, and ease of deployment, making it suitable for various food storage facilities. Rigorous testing ensures the reliability and accuracy of the system, and its implementation is intended to enhance food safety practices. Ongoing maintenance and updates are incorporated to ensure the sustained effectiveness of the monitoring solution in preventing food borne illnesses.

The cybersecurity mesh: A comprehensive survey of involved artificial intelligence methods, cryptographic protocols and challenges for future research

In today’s world, it is vital to have strong cybersecurity measures in place. To combat the ever-evolving threats, adopting advanced models like cybersecurity mesh is necessary to enhance our protection. Cybersecurity mesh is an architecture scalable, flexible, composable, robust and resilient and allows the interoperability and coordination between intelligent systems to provide security services. Designing a cybersecurity mesh faces three major challenges: scalability, distributed or federated systems, and technology integration. For the design, it is necessary to apply security tools that support scalability because millions and millions of data are stored, processed, and analysed. Federated systems are needed to improve interoperability in a decentralized cybersecurity mesh. However, it can be tough to integrate different security tools and communication protocols. Cryptographic algorithms and AI models like federated learning, swarming intelligence and blockchain technologies are useful for security services. It is essential to study the integration of existing methods to determine the best technology for the job. We conduct a comprehensive analysis of intelligent systems, including federated learning, blockchain technology, and swarming intelligence, with a particular focus on how they have been and can be used to enhance cybersecurity. We examine the latest trends in these technologies, explore their connections, and weigh the pros and cons of each approach. To conduct this review, we utilized the Web of Science and Scopus databases and followed the PRISMA guidelines.

BI-RRT*: An improved path planning algorithm for secure and trustworthy mobile robots systems

The optimal RRT in elliptic space sampling (Informed-RRT*) is an extension of RRT that provides asymptotic optimality, however, it experiences gradual progress and close to obstacles. In the paper, we propose a novel path planning algorithm guided bidirectional Informed-RRT* (BI-RRT*), that introduces extension range, dual-direction exploration, and refinement in trajectory design. The growth range refers to maintaining an additional area from the obstacle to enhance the dependability of the path through preventing impacts. Bidirectional search is a search strategy using both start and target points for a initial solution. Smoothing improves path robustness by using cubic spline. Furthermore, simulation tests for the BI-RRT* algorithm are executed, and the efficacy of the suggested algorithm is confirmed through its application in a robot operating system (ROS). Simulations and experimental tests verify that the proposed algorithm improves the path planning capability. We emphasize the importance of safety, privacy, and reliability in the deployment of AI systems. Our algorithm ensures that the planned paths maintain a safe distance from obstacles, reducing the risk of collisions. Additionally, we prioritize privacy by adhering to data protection regulations and implementing secure communication protocols within the AI system. Moreover, we have applied rigorous testing and validation processes to enhance the reliability of our algorithm, ensuring consistent and accurate path planning outcomes.

NFC Data Security Using Hill Cipher

Near Field Communication (NFC) technology has become ubiquitous in various applications, from contactless payments to data transfer between devices. As the use of NFC expands, ensuring the security of transmitted data becomes paramount. This research investigates the application of Hill Cipher, a linear algebra-based encryption technique, to enhance the security of data transmitted via NFC. In the field of contemporary wireless technology, near-field communication (NFC) stands out as an important force, enabling contactless transactions and the seamless exchange of information between electronic devices. This research explores the innovative integration of NFC into the attendance input process, which is linked to a website-based attendance system. NFC's adaptability, which was initially prominent in payment cards, has expanded across industries, empowering smartphones, tablets, and wearable devices. This study contributes to the ongoing development of NFC technology, proposing a renewable solution for student attendance systems. With a vision of increased efficiency, this research anticipates increased utilization of time and resources, thereby providing a promising path for the advancement of attendance management. A comprehensive evaluation of the proposed NFC data security solution was conducted through simulations and practical implementations. The research assesses the impact on communication speed, energy consumption, and overall system performance. Results indicate that the integration of Hill Cipher introduces a negligible overhead on communication speed, making it a viable option for real-time NFC applications. Furthermore, the study addresses potential vulnerabilities and threats associated with NFC technology, emphasizing the role of Hill Cipher in mitigating risks such as eavesdropping and unauthorized data interception. The research considers practical implementation challenges and proposes strategies for seamless integration into existing NFC-enabled devices. In conclusion, this research contributes to the ongoing discourse on NFC data security by introducing Hill Cipher as a robust encryption mechanism. The findings underscore the feasibility of implementing this encryption technique without compromising the efficiency of NFC communication. The proposed secure communication protocol holds promise for enhancing the privacy and integrity of data transmitted via NFC, fostering trust in the expanding ecosystem of NFC-enabled applications.

ML-based Intrusion Detection for Drone IoT Security

The integration of drones into various industries brings about cybersecurity challenges due to their reliance on internet connectivity. To address this, we propose a comprehensive cybersecurity architecture leveraging machine learning (ML) algorithms and Internet of Things (IoT) technologies within the Internet of Drones (IoD) framework. Our architecture employs IoT-enabled sensors strategically placed across the drone ecosystem to collect and analyze data on system behaviors, communication patterns, and environmental variables. This data is then processed by a centralized platform equipped with sophisticated ML algorithms for pattern identification and anomaly detection. A key feature is the dynamic learning mechanism, enabling real-time intrusion detection by adapting to evolving threats. By combining IoT and ML, the system proactively defends against cyberattacks by distinguishing between typical and abnormal activity. Emphasis is placed on data integrity and confidentiality through secure communication protocols and cryptographic algorithms. Extensive simulations and tests validate the framework's effectiveness in various IoD scenarios, demonstrating its ability to swiftly identify intrusions and informing future enhancements. This comprehensive study meticulously examines the pressing cybersecurity concerns within the burgeoning drone industry. It proposes a robust architectural framework designed to enhance security for drone-enabled applications in our increasingly interconnected world. By harnessing the synergies between Internet of Things (IoT) and Machine Learning (ML) technologies, this innovative approach aims to fortify the integrity and reliability of drone systems.

A Lightweight and Secure Communication Protocol for the IoT Environment

Ensuring secure communications for the Internet of Things (IoT) systems remains a challenge. Due to exacting resource limitations of computing, memory, and communication in IoT environments, communication schemes based on asymmetric cryptographic systems can be challenging to deploy. An alternative is to deploy symmetric encryption schemes based on pre-shared keys. However, there are also challenges in designing such schemes and examples include how to achieve an optimal trade-off between security and performance levels while meeting resource consumption requirements. Hence, this paper presents a lightweight key synchronization update algorithm, which is then used as a building block in our proposed lightweight secure communication protocol. The security of the protocol is analyzed to show that it can resist common attacks, such as replay attacks, and man-in-the-middle attacks. We then use Tamarin, a widely accepted security protocol verification tool, for formal verification. In addition, we evaluate the randomness and computational performance of the lightweight key synchronization update algorithm and demonstrate that it outperforms other schemes. We also evaluate the performance of the protocol, in terms of computational and communication costs, to demonstrate utility.