Secure Communication Channel Research Articles

Exploring Quantum Entanglement for Secure Communication: A Study on Quantum Cryptography Protocols

Quantum Ensnarement, a wonder at the heart of quantum mechanics, has risen as a promising road for revolutionizing secure communication through Quantum Cryptography. This inquiries about digs into the investigation of Quantum Ensnarement as an establishment for creating vigorous and secure communication conventions. The think about includes an in-depth examination of different Quantum Cryptography conventions, exploring their hypothetical underpinnings and viable executions. The investigate strategy utilizes a combination of hypothetical modeling and exploratory approval to survey the viability and security of Quantum Cryptography conventions in assorted scenarios. Key angles beneath investigation incorporate the era, conveyance, and utilization of snared particles to build up secure communication channels. Quantum key dispersion (QKD) conventions, such as BB84 and E91, will be inspected in detail to comprehend their qualities, vulnerabilities, and potential for commonsense execution in real-world communication frameworks. Moreover, the inquire about investigates the challenges and progressions in quantum innovation that contribute to the effective arrangement of Quantum Cryptography conventions.

Implementation of a novel secured authentication protocol for cyber security applications

Robust verification protocols are crucial for maintaining the security and reliability of sensitive information due to the increasing complexity of cyber-attacks. This paper introduces a novel 5G Secure Handover Protocol aimed at addressing security and effectiveness issues encountered in existing systems. The proposed protocol is robust against various attacks, including de-synchronization, replay, man-in-the-middle (MITM), denial of services (DoS), and jamming, ensures perfect forward key secrecy, safeguarding communication confidentiality. The proposed protocol utilizes a combination of spiking neural network and fuzzy logic (SNN-FL) techniques that must choose the goal cell as carefully as possible before initiating the transfer process. By combining fuzzy logic and spiking neural networks to reduce handover latency and thwart several types of cyberattacks, the proposed 5G Secure Handover Protocol improves security. Extensive simulations show its efficacy and emphasize its potential for safe communication in large-scale cybersecurity applications. The paper presents a novel secure authentication protocol that significantly reduces handover delays and improves efficiency. Simulations show its resilience against common security threats, protecting sensitive information and maintaining secure communication channels. The protocol, with low communication expenses, complex spatial, and latency for changeover verification, is ideal for large-scale cybersecurity applications, contributing to the development of secure digital authentication mechanisms.

RescueNow: Real-time SOS and Predictive Women's Safety System

This paper presents a comprehensive women’s safety application designed to address the growing concerns of personal safety through technological intervention. The system integrates multiple advanced features such as real-time SOS alerts, geofencing to detect high-risk areas, AI-driven crime predictions, and multiple SOS activation methods, including voice commands, shake detection, and button press. Additionally, the app employs silent recording functionality to gather evidence in distress situations and incorporates secure communication channels for contacting law enforcement. The application also supports community-driven safety ratings and crime reporting. Tested with real-world scenarios, the system demonstrates high accuracy in predictive analytics and provides a seamless, scalable solution for enhancing women’s safety. This project contributes to the field of personal safety technologies by introducing a multi-faceted, AI-enabled framework for real-time risk mitigation. Key Words: Women’s safety, SOS alerts, AI crime prediction, geofencing, real-time GPS tracking, predictive analytics, Firebase Cloud Messaging, Twilio, silent recording, crime reporting.

Mechanisms for Securing Autonomous Shipping Services and Machine Learning Algorithms for Misbehaviour Detection

Technological developments within the maritime sector are resulting in rapid progress that will see the commercial use of autonomous vessels, known as Maritime Autonomous Surface Ships (MASSs). Such ships are equipped with a range of advanced technologies, such as IoT devices, artificial intelligence (AI) systems, machine learning (ML)-based algorithms, and augmented reality (AR) tools. Through such technologies, the autonomous vessels can be remotely controlled from Shore Control Centres (SCCs) by using real-time data to optimise their operations, enhance safety, and reduce the possibility of human error. Apart from the regulatory aspects, which are under definition by the International Maritime Organisation (IMO), cybersecurity vulnerabilities must be considered and properly addressed to prevent such complex systems from being tampered with. This paper proposes an approach that operates on two different levels to address cybersecurity. On one side, our solution is intended to secure communication channels between the SCCs and the vessels using Secure Exchange and COMmunication (SECOM) standard; on the other side, it aims to secure the underlying digital infrastructure in charge of data collection, storage and processing by relying on a set of machine learning (ML) algorithms for anomaly and intrusion detection. The proposed approach is validated against a real implementation of the SCC deployed in the Livorno seaport premises. Finally, the experimental results and the performance evaluation are provided to assess its effectiveness accordingly.

Critical Value Reporting Performance Improvement Initiative: A Journey Towards Timely Patient Safety

Abstract Timely reporting of critical values serves as a quality indicator for the National Patient Safety Goal. Since the oncology inpatient unit at our institution has the highest number of critical values and often struggles to meet the targeted goal of timely results acknowledgement, this prompted a performance improvement initiative. By utilizing the Institute for Healthcare Improvement (IHI) Model for Improvement, the study aimed to decrease the time from specimen collection to acknowledgment of a complete blood count critical values (overall TAT). Three key metrics were monitored, including unit turnaround time (time from collection to receipt in laboratory; uTAT), laboratory turnaround time (time from receipt in laboratory to verified results) and timely critical value acknowledgment rate (% acknowledgement within 30 minutes). Quality improvement tools such as process maps and fishbone diagrams were employed, and two areas for improvement were identified. Firstly, it was observed that samples collected by the phlebotomists were delivered in batch to the laboratory via carts. However, samples collected by nurses were sent to the laboratory via a pneumatic tube. Hence, the uTAT varied drastically due to the different delivery methods. Secondly, the mode of alerting providers regarding critical values, which was via telephone calls from telecommunication staff, was deemed disruptive and redundant, as the providers often were already aware of the results from the electronic medical record (EPIC). Two multi-cycle Plan-Do-Study-Act (PDSA) interventions were implemented by a multidisciplinary team. The first focused on sending samples via pneumatic tube. The second PDSA intervention focused on a direct clinician acknowledgment of critical values within EPIC, by creating an auxiliary column on the EPIC patient list. Consequently, the overall TAT decreased from a median time of 167 minutes in July 2021 to 140 minutes by March 2022 in the oncology inpatient unit, with a sustained result (139 minutes) by October 2023. This reduction was driven by the standardization of pneumatic tube delivery system; the uTAT decreased from a median time of 104 minutes to 46 minutes by March 2022 and remained low at 52 minutes by January 2024. Notably, the rate of timely acknowledgment of critical value results worsened, dropping from 67% to as low as 51 % (March 2022) and improved to 64% by January 2024. It was realized that this unintended consequence was attributed to the decrease in uTAT, leading to more critical value results reported in early morning when there was less staffing. Despite the worsening in timely critical value acknowledgment, the overall TAT showed a discernible reduction. The application of IHI methodology played a pivotal role in expediting result reporting. Subsequent steps will focus on utilizing secure communication channels to augment the success rate of critical values acknowledgment within 30 minutes.

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.

Efficient provable dual receiver hybrid and light weight public key schemes based on the discrete logarithm problem without pairings

AbstractDual‐receiver proxy re‐encryption is a cryptographic technique that enables secure data sharing among multiple authorized users or entities. It has gained significant attention for its ability to manage access permissions, data confidentiality, and streamline communication channels. These schemes have been widely used in various applications, including healthcare systems, cloud computing, Internet of Things (IoT) systems, collaborative environments, and secure communication channels. This paper aims to propose two proxy re‐encryption schemes for dual receivers without pairings. The first is dual receiver lightweight proxy re‐encryption without pairings (DR‐LWPRE‐WP), which uses a public key scheme to reduce computational complexity. The second is dual receiver hybrid proxy re‐encryption without pairings (DR‐HPRE‐WP), which incorporates public key and symmetric key schemes. Both schemes offer protection against selected plaintext attacks based on the decisional Diffie‐Hellman principle. The DR‐LWPRE‐WP scheme reduces computation by approximately 53% compared to pairing‐based schemes, making it suitable for lightweight applications like the Internet of Things. The computational efficacy of these schemes offers significant benefits for resource‐constrained environments and practical implementations.

Advanced error correction method for quantum key distribution in IoT systems

The secure distribution of keys is essential to ensuring the privacy and integrity of data in Internet of Things (IoT) systems. Quantum Key Distribution (QKD) protocols, such as BB84, use principles from quantum mechanics to establish secure communication channels. However, errors that occur during the transmission of qubits can compromise the reliability of the shared key. This paper presents a new method for error correction that integrates Convolutional Neural Networks (CNNs) into the BB84 protocol for QKD in IoT systems. By harnessing the exceptional pattern recognition capabilities of CNNs, our approach learns hierarchical representations from preprocessed quantum channel data to effectively identify and correct errors. Extensive simulations demonstrate the high performance of our CNN-based method in reducing the Quantum Bit Error Rate (QBER). This contribution significantly enhances the security and reliability of key distribution, offering a promising solution for robust quantum communication in IoT environments.

Dual Authentication on a Secure Communication Channel to Image Transmission

Dual Authentication on a Secure Communication Channel to Image Transmission

IoT IP Overlay Network Security PerformanceAnalysis with Open Source Infrastructure Deployment

Some of the most deployed infrastructures nowadays are Overlay Networks (ONs). They consist of hardware and software components designed to establish private and secure communication channels, typically over the Internet. ONs are among the most reliable technologies for achieving this objective and represent the next-generation solution for secure communication. In this paper, we analyze important network performance metrics (RTT, bandwidth) while varying the type of Overlay Network used for interconnecting traffic between two or more hosts (within the same data center, in different data centers in the same building, or over the Internet). These networks establish connections between KVM (Kernel-based Virtual Machine) instances rather than the typical Docker/LXC/Podman containers. The first analysis will assess network performance as it is, without any overlay channels. The second will establish various types of channels without encryption, and the final one will encapsulate overlay traffic via IPsec (Transport mode), where encrypted channels like VTI are not already available for use. The obtained performance is demonstrated through a comprehensive set of traffic-simulation campaigns.

COLOR IMAGE ENCRYPTION THROUGH MULTI-S-BOX GENERATED BY HYPERCHAOTIC SYSTEM AND MIXTURE OF PIXEL BITS

The growing demand for maintaining secure communication channels with the advancements in digital technologies has led to an intensified interest in designing reliable image encryption schemes. Despite various encryption schemes that have been used, some are considered to have insecurity regarding data transmission and multimedia. Motivated by this concern, this paper proposes a new color image encryption algorithm of a multi-key generation-based nD-Hyperchaotic (HC) system. The new algorithm achieves Shannon’s confusion and diffusion principles using a two S-box generation approach, where the first S-box is generated from the proposed nD-HC system and the resulting sequence is used to increase encryption complexity, while the second S-box is generated from ([Formula: see text])D-HC system. Afterward, mathematical analysis is carried out to showcase the robustness and efficiency of the proposed algorithm, as well as its resistance to visual, statistical, differential, and brute-force attacks. The proposed scheme successfully passes all NIST SP 800 suite tests. The cryptographic system demonstrated by the proposed scheme has proven to have outstanding performance through simulation tests, which indicates promising potential applicability aspects in secure and real-time image communication settings.

S-ZAC: Hardening Access Control of Service Mesh Using Intel SGX for Zero Trust in Cloud

In cloud services, the zero-trust security paradigm has emerged as a key strategy to reduce the large attack surface created by the complexity of cloud systems. Service mesh is a popular practice to realize the zero-trust architecture, which relies heavily on network access control to achieve the desired security. Building a service mesh-based solution in the cloud is not straightforward because privileged adversaries (e.g., malicious cloud insiders) can easily compromise the control plane where the access control function is implemented. In this paper, we propose S-ZAC, an access control hardening technique for service mesh-based solutions in the cloud. S-ZAC uses Intel SGX to provide a trusted execution environment for the control plane, which is responsible for enforcing access control for the service mesh. By isolating all access-control-related functions within an SGX enclave, S-ZAC ensures high resilience of the service mesh solution even in the presence of privileged adversaries. Due to the design limitations of SGX, implementing S-ZAC in the cloud for zero trust faces several challenges that can lead to serious scalability and failover issues. The first challenge is to establish secure communication channels between the S-ZAC components, even in the presence of privileged attackers. The second challenge is the limited memory capacity of the SGX enclave. Finally, the third challenge is that the inherent design of SGX does not support persistent enclave states, meaning that any state of running enclaves is volatile. We address these challenges by proposing our novel solutions. By implementing a prototype of S-ZAC, we evaluate its performance in terms of security and performance. The evaluation results validate the effectiveness of S-ZAC to enhance the security of the service mesh control plane in cloud environments.

A Secure Authentication Scheme with Local Differential Privacy in Edge Intelligence-Enabled VANET

Edge intelligence is a technology that integrates edge computing and artificial intelligence to achieve real-time and localized model generation. Thus, users can receive more precise and personalized services in vehicular ad hoc networks (VANETs) using edge intelligence. However, privacy and security challenges still exist, because sensitive data of the vehicle user is necessary for generating a high-accuracy AI model. In this paper, we propose an authentication scheme to preserve the privacy of user data in edge intelligence-enabled VANETs. The proposed scheme can establish a secure communication channel using fuzzy extractor, elliptic curve cryptography (ECC), and physical unclonable function (PUF) technology. The proposed data upload process can provide privacy of the data using local differential privacy and symmetric key encryption. We validate the security robustness of the proposed scheme using informal analysis, the Real-Or-Random (ROR) model, and the Scyther tool. Moreover, we evaluate the computation and communication efficiency of the proposed and related schemes using Multiprecision Integer and Rational Arithmetic Cryptographic Library (MIRACL) software development kit (SDK). We simulate the practical deployment of the proposed scheme using network simulator 3 (NS-3). Our results show that the proposed scheme has a performance improvement of 10∼48% compared to the state-of-the-art research. Thus, we can demonstrate that the proposed scheme provides comprehensive and secure communication for data management in edge intelligence-enabled VANET environments.

Exploring the fusion of lattice‐based quantum key distribution for secure Internet of Things communications

AbstractThe integration of lattice‐based cryptography principles with Quantum Key Distribution (QKD) protocols is explored to enhance security in the context of Internet of Things (IoT) ecosystems. With the advent of quantum computing, traditional cryptographic methods are increasingly susceptible to attacks, necessitating the development of quantum‐resistant approaches. By leveraging the inherent resilience of lattice‐based cryptography, a synergistic fusion with QKD is proposed to establish secure and robust communication channels among IoT devices. Through comprehensive Qiskit simulations and theoretical analysis, the feasibility, security guarantees, and performance implications of this novel hybrid approach are thoroughly investigated. The findings not only demonstrate the efficacy of lattice‐based QKD in mitigating quantum threats, but also highlight its potential to fortify IoT communications against emerging security challenges. Moreover, the authors provide valuable insights into the practical implementation considerations and scalability aspects of this fusion approach. This research contributes to advancing the understanding of quantum‐resistant cryptography for IoT applications and paves the way for further exploration and development in this critical domain.

Enhancing cybersecurity protocols in the era of big data and advanced analytics

In the modern digital landscape, the exponential growth of big data and the proliferation of advanced analytics present both unprecedented opportunities and significant challenges for cybersecurity. This review explores the imperative of enhancing cybersecurity protocols to safeguard sensitive information and ensure the integrity of digital infrastructures in an era characterized by vast data generation and sophisticated analytical techniques. As organizations across various sectors leverage big data to drive innovation and gain competitive advantages, they simultaneously face heightened risks from cyber threats. Advanced analytics, including machine learning and artificial intelligence, offer potent tools for detecting and mitigating these threats. However, the integration of such technologies into cybersecurity frameworks demands a comprehensive and forward-thinking approach. Key to this enhancement is the development of robust data governance policies that ensure data integrity, confidentiality, and availability. These policies must address the complexities introduced by diverse data sources, varied data formats, and the velocity at which data is generated and processed. Additionally, the implementation of machine learning algorithms can significantly improve threat detection capabilities by identifying patterns and anomalies indicative of cyber threats, thus enabling proactive defense mechanisms. Moreover, enhancing cybersecurity protocols involves the adoption of encryption techniques and secure communication channels to protect data both at rest and in transit. Continuous monitoring and real-time analytics are crucial for maintaining situational awareness and promptly responding to potential breaches. The utilization of big data analytics also facilitates the identification of vulnerabilities and the assessment of risk profiles, allowing for the prioritization of security measures based on threat severity and impact. Despite the technological advancements, challenges such as data privacy concerns, algorithmic biases, and the need for skilled cybersecurity professionals persist. Addressing these challenges requires a multi-faceted strategy encompassing regulatory compliance, ethical considerations, and ongoing education and training. In conclusion, enhancing cybersecurity protocols in the era of big data and advanced analytics is essential for protecting critical digital assets and maintaining trust in digital ecosystems. By integrating cutting-edge analytical tools and establishing comprehensive data governance frameworks, organizations can effectively mitigate cyber risks and leverage the full potential of big data for sustainable growth and innovation.

Privacy-Centric AI and IoT Solutions for Smart Rural Farm Monitoring and Control.

The integration of artificial intelligence (AI) and the Internet of Things (IoT) in agriculture has significantly transformed rural farming. However, the adoption of these technologies has also introduced privacy and security concerns, particularly unauthorized breaches and cyber-attacks on data collected from IoT devices and sensitive information. The present study addresses these concerns by developing a comprehensive framework that provides practical, privacy-centric AI and IoT solutions for monitoring smart rural farms. This is performed by designing a framework that includes a three-phase protocol that secures data exchange between the User, the IoT Sensor Layer, and the Central Server. In the proposed protocol, the Central Server is responsible for establishing a secure communication channel by verifying the legitimacy of the IoT Sensor devices and the User and securing the data using rigorous cryptographic techniques. The proposed protocol is also validated using the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The formal security analysis confirms the robustness of the protocol and its suitability for real-time applications in AI and IoT-enabled smart rural farms, demonstrating resistance against various attacks and enhanced performance metrics, including a computation time of 0.04 s for 11 messages and a detailed search where 119 nodes were visited at a depth of 12 plies in a mere search time of 0.28 s.

Fostering social media user intentions: AI-enabled privacy and intrusiveness concerns

Purpose This paper aims to empirically examine the impact of psychological factors (i.e. privacy and intrusiveness concerns) on user intentions regarding artificial intelligence (AI)-enabled social commerce applications at their core through perceived usefulness. The theoretical model is supported by the theory of planned behaviour (TPB). Design/methodology/approach Data was gathered from 488 social media users in Saudi Arabia. Findings Privacy concerns significantly affect perceived usefulness. Furthermore, the link between privacy concerns and behavioural intentions was mediated by perceived usefulness. Research limitations/implications Business leaders should raise users’ awareness about the effectiveness of AI-powered tools that can influence their behavioural intentions. Furthermore, managers must be aware of the regulations that protect user privacy, track online activity and offer secure communication channels. Originality/value This paper expands on TPB by bridging the theoretical and practical divide. It further develops a theoretical framework for practitioners to better understand customers’ physiological aspects of using AI-powered social commerce platforms.

Internet of Things (IoT) Data Communication Challenges, and Solutions

IoT has become an integral part of our lives, and data communication is one of the most important aspects of IoT. IoT devices can exchange data with each other via secure communication channels. This study aimed to review the IoT data communication challenges and solutions This paper attempts to address the key challenges and solutions for effective IoT data communication, starting by exploring the current challenges of IoT data communication related to scalability, reliability, and security, potential solutions to these challenges, such as using a mesh network, centralized servers, and edge computing. In addition, the paper discusses the importance of proper authentication and authorization techniques to ensure secure communication between IoT devices. The potential of IoT data communication is vast and has the power to fundamentally transform our society. It is an exciting time to be involved in this field, and the future looks promising for the advancement of IoT data communication.

A heterogeneous signcryption scheme with Cryptographic Reverse Firewalls for IoT and its application

The Snowden leaks exposed the truth that skilled attackers can access users’ devices and steal their private information. Although public key encryption is widely used and theoretically secure, it has hidden vulnerabilities when implemented in practice. This is especially problematic when employing communication channels among heterogeneous protocols within the Internet of Things (IoT), it becomes apparent that these channels lack adequate protection to address the diverse nature of IoT systems. This work proposes a novel Heterogeneous Online/Offline Signcryption with Cryptographic Reverse Firewalls (HOOS-CRF). The scheme enables a secure communication channel between the sender in an Identity-based cryptosystem (IBC) and the receiver in the Public Key Infrastructure (PKI) cryptosystem with CRF deployed. To reduce computational costs, we split the signcryption algorithm into two stages: online and offline. Most resource-intensive operations are performed during the offline stage, which operates without any knowledge of the message being processed. The HOOS-CRF scheme provides confidentiality, authentication, and defense against insider security attacks. Meanwhile, we prove the security of the HOOS-CRF using the random oracle model and demonstrate its high efficiency and practicality through experiments. Lastly, the scheme’s relevance to IoT-driven healthcare applications is demonstrated.

HSM4SSL: Leveraging HSMs for Enhanced Intra-Domain Security

In a world where digitization is rapidly advancing, the security and privacy of intra-domain communication within organizations are of critical concern. The imperative to secure communication channels among physical systems has led to the deployment of various security approaches aimed at fortifying networking protocols. However, these approaches have typically been designed to secure protocols individually, lacking a holistic perspective on the broader challenge of intra-domain communication security. This omission raises fundamental concerns about the safety and integrity of intra-domain environments, where all communication occurs within a single domain. As a result, this paper introduces HSM4SSL, a comprehensive solution designed to address the evolving challenges of secure data transmission in intra-domain environments. By leveraging hardware security modules (HSMs), HSM4SSL aims to utilize the Secure Socket Layer (SSL) protocol within intra-domain environments to ensure data confidentiality, authentication, and integrity. In addition, solutions proposed by academic researchers and in the industry have not addressed the issue in a holistic and integrative manner, as they only apply to specific types of environments or servers and do not utilize all cryptographic operations for robust security. Thus, HSM4SSL bridges this gap by offering a unified and comprehensive solution that includes certificate management, key management practices, and various security services. HSM4SSL comprises three layers to provide a standardized interaction between software applications and HSMs. A performance evaluation was conducted comparing HSM4SSL with a benchmark tool for cryptographic operations. The results indicate that HSM4SSL achieved 33% higher requests per second (RPS) compared to OpenSSL, along with a 13% lower latency rate. Additionally, HSM4SSL efficiently utilizes CPU and network resources, outperforming OpenSSL in various aspects. These findings highlight the effectiveness and reliability of HSM4SSL in providing secure communication within intra-domain environments, thus addressing the pressing need for enhanced security mechanisms.