Secure Communications In Networks Research Articles

UAV COMMUNICATION PROTOCOLS AND QUALITY OF SERVICE IN 5G COMMUNICATION

This paper aims to provide an overview of common network protocols in UAV communications with a focus on security and vulnerabilities. In order to assess the common types of vulnerabilities, various elements must be taken into account such as mission purpose, communication type and protocol. The paper will walk through the main types of UAV protocols and make a brief analysis in terms of communication network security. It will also look on 5G communication requirements in terms of quality of service.

A hybrid CNN-GRU-based intrusion detection system for secure communication in vehicular adhoc network

ABSTRACT Vehicular Ad hoc Network (VANET) is a component of the Intelligent Transportation System (ITS) which furnishes communication among vehicles. It delivers comfort and safety information to passengers and vehicle drivers. Security plays a vital role during the transmission of data as the various distinct security attacks directly influence the safety of the passengers on the road. Several security attacks will disrupt normal functions like the transmission of data. Some security breaches inject false information which affects the safety of drivers. However, there are several demurrers in detecting abnormal activities efficiently as the traditional system faces imbalanced data problems. This paper presents an Intrusion Detection System (IDS) for detecting anomalies and protecting communication systems from several distinct attacks. The proposed IDS utilizes two deep learning (DL) mechanisms such as Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) for detecting anomalies in the vehicular network. The hybrid CNN-GRU mechanism helps in solving the overfitting and low-velocity problems. It also detects several attacks and protects the ad hoc network from those attacks to safeguard the vehicle users. The results show that the propounded model outperforms the other traditional detection mechanisms by 10.79% in terms of performance compared to other IDS.

Application of Intelligent Cloud Computing Technology in Optical Communication Network Security of Smart Grid

In order to improve the security of smart grid optical communication network, this paper combines intelligent cloud computing technology to build a security system of optical communication network of power grid. In the aspect of improving communication security performance, multi-user access is realized by non-orthogonal power domain segmentation, and different users use different powers to add and superimpose the same spectrum resources, so as to increase spectrum utilization. At the sending end, this paper improves the safe channel capacity of users by means of pre-coding and artificial noise, and realizes the safe transmission of information. In terms of transmission stability, the cloud computing platform is used as a data processing platform, and multiple nodes are processed synchronously through optical communication state identification, which can more effectively improve the speed of optical communication state identification data. In order to test the performance of the power grid information dispatching model designed in this paper in optimizing power grid configuration and improving power grid load, simulation experiments are carried out. Through the experimental analysis, we can see that the communication method proposed in this paper can accurately identify the intrusion factors, and can effectively improve the security of smart grid optical communication network.

Strategic Approaches in Network Communication and Information Security Risk Assessment

Strategic Approaches in Network Communication and Information Security Risk Assessment

Research on Communication Network Security Based on Narrowband Internet of Things and Encryption Algorithms

With the rapid development of Internet of Things (IoT) technology, Narrowband IoT (NB-IoT) has been widely adopted in smart cities, smart homes, and industrial automation due to its low power consumption, wide coverage, low cost, and high reliability. However, the associated security issues have become a critical factor hindering its further development. This paper aims to explore the security challenges in NB-IoT communication networks using encryption algorithms. Through theoretical analysis and model construction, a comprehensive security solution is proposed. Initially, the paper reviews the fundamental principles and application scenarios of NB-IoT, analyzing the current challenges in network security, including data leakage, device tampering, and man-in-the-middle attacks. Subsequently, a security framework based on lightweight encryption algorithms is introduced, leveraging the strengths of both symmetric and asymmetric encryption to ensure security while reducing computational and communication overheads. Additionally, the application of blockchain technology in NB-IoT security is discussed, enhancing data credibility and system resilience against attacks through its decentralized nature. Theoretical derivations and simulation analyses confirm the effectiveness and feasibility of the proposed security framework. The results demonstrate that this framework significantly enhances the security performance of NB-IoT networks, providing theoretical support and practical guidance for the secure development of IoT.

Research on the Application of Data Encryption Technology in Computer Network Communication Security

With the rapid development of information technology, computer network communication has been widely used in various fields. However, the security issues of network communication have become increasingly prominent, and data is vulnerable to various attacks during transmission. Data encryption technology is a key technology for protecting information security. By converting plaintext information into non-mandatory ciphertext, the confidentiality and non-threatening nature of data are protected. This paper first introduces the basic principles and classification of data encryption technology, including real-time encryption, real-time encryption and hybrid encryption. It mainly analyzes the specific applications of data encryption technology in virtual private networks (VPNs), secure gateway security layers (SSL)/transport layer security (TLS), wireless network security, email encryption and cloud storage encryption. Finally, the development trends of emerging technologies such as quantum encryption, homomorphic encryption and blockchain encryption are discussed. By reasonably applying these encryption technologies, the security of computer network communication can be effectively improved.

Text and Image Encryption using ECC

This project combines Elliptic Curve Cryptography (ECC) with Random Matrix Cryptography (RMC) for image encryption and ECC with the Lorenz algorithm to provide a comprehensive solution to data security. Chaotic equation for text encryption. While ECC-Lorenz uses chaotic dynamics for text encryption, ECC-RMC uses matrix operations to strengthen image encryption. The efficacy of both strategies in safeguarding the confidentiality and integrity of transmitted data is demonstrated through experimental validation, which therefore improves network communication security. A multi-layered encryption architecture is established by the integration of ECC-RMC and ECC-Lorenz, providing a strong defense against cyber attacks and unlawful access. This new encryption paradigm promises improved resilience in digital information transfer, marking a significant leap in data security measures. The suggested method gives a flexible way to combine computational complexity and mathematical rigor

Error correction based artificial neural network in multi-modes CV-QKD with simultaneous type-I and type-II parametric-down conversion entangled photon source

We model simultaneous type-I and type-II phase matching in a single non-linear crystal (NLC), based on a double periodically poled lithium niobate crystal. We also discuss entanglement based continuous variable quantum key distribution (CV-QKD), and the security of such scheme is analyzed considering an eavesdropper being capable of individual attacks. We further demonstrate efficiency of the artificial neural network (ANN) algorithm during post-processing or errors correction in such CV-QKD protocols. Results show that employing simultaneous type-I and type-II SPDC process in single NLC is a potential source to generate high dimensional (or hyper-entangled) states, strongly required for quantum information processing tasks, an example of CV-QKD. Security analysis of such a CV-QKD protocol shows a strong advantage of employing the above entangled photon state source, given that it provides a higher secure key rate and thus a secure communication within a larger distance. In addition, the suggested error correction algorithm is less time consuming and highly efficient, since full synchronization is achieved just after a few number of updates of trusted parties’ tree-parity-machines. Our results sufficiently demonstrate that the suggested CV-QKD is able to distribute secure keys in nearby inter-city areas, and therefore allows lower-cost secure communication networks.

Communication network security situation analysis based on time series data mining technology

AbstractCommunication network security situation analysis prevents unauthorized users from accessing and stealing sensitive information. Network security analysis aims to monitor, discover, and eradicate security flaws by carefully examining the network’s architecture, data, and traffic to ensure safety. In time series data mining analysis by cyber terrorism, specialists must pay attention to cyber security, which involves identifying the elements contributing to long-term trends or systemic patterns via pattern-matching algorithms and other types of inferential processing on large datasets. The challenging characteristics of communication network security situation analysis are data loss, security breaches, hacking, and viruses. Hence, in this research, attention mechanism-based convolutional neural network-enabled practical byzantine fault tolerant (AMBCNN-PBFT) has been designed to improve communication network security situation analysis in time series data mining. AMBCNN-PBFT helps to increase communication network security usage and support the expansion during the evaluation system by optimizing the time series data mining. AMBCNN-PBFT effectively predicts the rise in the communication network, associated with faster times series benefits data mining approach. The study concludes that the AMBCNN-PBFT efficiently indicates and validates the communication network security in time series data mining during the evaluation system. The experimental analysis of AMBCNN-PBFT outperforms the data mining time series in terms of accuracy, efficiency, performance, and prediction.

An efficient online/offline heterogeneous proxy signcryption for secure communication in UAV networks

The rapid growth of the Internet of Things (IoT) has led to an increased deployment of unmanned aerial vehicles (UAVs) across various sectors. However, efficiency and security issues are persistently among the primary challenges in UAV networks. In addition, significant communication delays can occur when UAVs perform remote tasks far from a command center (CC); in some cases, they may be unable to communicate with the CC. To address these challenges, in this paper, an efficient online/offline heterogeneous proxy signcryption scheme for secure communication in UAV networks (HOOPSC) is proposed. This scheme enables the CC in a certificateless cryptosystem (CLC) environment to delegate a nearby ground control station (GCS) to act as an agent, and directly send commands to the UAV within an identity-based cryptosystem (IBC) when the UAV undertakes remote tasks far from the CC. The UAV then decrypts and verifies commands for authenticity and confidentiality. In the proposed scheme, the signcryption process is split into offline and online phases, with most of the heavy computations conducted without the availability of the messages during the offline phase. Only light computations are performed in the online phase when a message is available. Moreover, a formal security proof is given in a random oracle model. Finally, a performance analysis reveals that HOOPSC outperforms existing relevant schemes, making it ideal for long-range operations in UAV networks.

Enhancing Efficiency and Security in MTC Environments: A Novel Strategy for Dynamic Grouping and Streamlined Management

This study presents a new strategy to improve security and efficiency in Machine-Type Communication (MTC) networks, addressing the drawbacks of the existing Adaptive Hierarchical Group-based Mutual Authentication and Key Agreement (AHGMAKA) protocol. The AHGMAKA protocol, crucial for securing communication within groups of devices with limited resources, has been found to cause significant operational delays and inefficiencies. Our proposed solution integrates advanced cryptographic methods, including an optimized Authenticated Message Authentication Code (AMAC) and lightweight encryption, sophisticated optimization algorithms for dynamic grouping, and an efficient, lightweight group management protocol. It also introduces adaptive network management strategies to customize performance according to the needs of MTC networks. The effectiveness of this approach has been validated through empirical analysis, showing considerable improvements in operational performance and energy efficiency. These improvements mark a significant step toward achieving an optimal balance between efficiency and security for MTC networks. However, the research acknowledges ongoing challenges, including the trade-off between security and efficiency and the issue of compatibility with older devices, suggesting these as areas for future study. The paper outlines potential research paths, including using machine learning for better group management, adopting post-quantum cryptographic methods, applying hardware acceleration, and pushing to standardize these technologies. This work significantly advances the field of secure and efficient communication in MTC, a critical component of the growing Internet of Things (IoT) landscape, setting the stage for future breakthroughs.

VIRTUAL PRIVATE NETWORKS (VPN): A CONCEPTUAL REVIEW OF SECURITY PROTOCOLS AND THEIR APPLICATION IN MODERN NETWORKS

Virtual Private Networks (VPNs) play a crucial role in ensuring secure communication over public networks. This concept paper provides a comprehensive review of security protocols used in VPNs and their application in modern networks. The paper begins by defining VPNs and explaining their importance in securing data transmission over untrusted networks. It then discusses the evolution of VPN technology, highlighting the transition from traditional IPSec and SSL/TLS protocols to more modern approaches such as WireGuard and QUIC. The paper also examines the security protocols used in VPNs, including IPSec, SSL/TLS, and the newer protocols like WireGuard and QUIC. Each protocol is analyzed in terms of its security features, performance, and suitability for different use cases. Furthermore, the paper explores the application of VPNs in modern networks, including their use in remote access, site-to-site connectivity, and securing cloud-based services. It also discusses the challenges and considerations involved in deploying and managing VPNs in today's complex network environments. In conclusion, the paper emphasizes the importance of VPNs in ensuring secure communication in modern networks. It highlights the need for organizations to carefully evaluate their VPN requirements and choose the appropriate security protocols and technologies to protect their data and networks. Keywords: VPN, Security, Applications, Network.

IoT-Driven solutions for VANET trustworthiness: Examining misconduct and position security challenges

Vehicular ad hoc networks (VANETs) improve the traffic management and road safety by exchanging real-time data between automobiles and roadside infrastructure. Reliable Intelligent Transport Systems (ITS) solutions tend to boost VANET data security, integrity and dependability. These systems communicate VANET data between infrastructure and automobiles using sensors, Internet of Things (IoT) devices and communication technologies. IoT-driven includes a Real-Time Traffic Observation optimizes VANET route design. Traffic management and safety improve with ITS-connected cars and infrastructure. Remote communication technologies enhance traffic management and decision-making by sending a real-time data between cars and infrastructure. Smart parking systems use real-time parking availability data from IoT sensors and devices to maximize space use and reduce congestion. Security and misbehavior are dependable problems in 40 IoT-driven VANET studies. Miscommunication and unstandardized are the main security issues which pose hazards. This review shows VANETs that requires authentication, encryption and anomaly detection to prevent attacks and IoT for transportation sector. This extensive review covers VANET reliability and IoT-driven real-time traffic monitoring, ITS, remote communication and intelligent parking systems. This review analyzes the metrics to assess the many detection techniques which includes, misconduct-Aware On-Demand Collaborative Intrusion Detection System (MACIDS) and Collision-Induced Dissociation Spectroscopy (CIDS), (i) Accuracy (ii) False Positive Rate, (iii) precision, (iv) recall (v) False Negative Rate and (vi) F1-Score in VANET security in Attack Detection Rates (ADR), misbehavior detection, evaluation metrics and detection algorithms were studied using CIC-IDS data. Due to misconduct and security issues, a strong IoT-driven solutions are required to improve VANET trustworthiness and offers a secure and reliable vehicular communication networks for safer and more efficient transportation systems.

Research on Information Security of Communication Network between Electric Vehicle and Charge Point

In view of the information security issues in the communication network between electric vehicles and charging piles, this study analyzes the information security risks existing in the communication network between electric vehicles and charging piles, expounds the charging process between electric vehicles and charging piles, and assesses the risks existing in the charging piles.

Radio Contra Harmonic Mean Number of Graphs

Objectives: To explore the least upper bound of graphs by radio contra harmonic labeling. Methods: Contra harmonic mean function or , radio mean labeling condition and radio harmonic mean labeling are used. Findings: Here we introduce radio contra harmonic mean labeling and its least upper bound, designated as radio contra harmonic mean number, by formulating the constraints. Novelty: Based on radio mean labeling and contra harmonic mean labeling, the new concept of radio contra harmonic mean labeling was established. The bounds of some special graphs are encountered here. This kind of labeling is employed in secure communication networks and is also applicable in X-rays, crystallography, coding theory, computing etc. Keywords: Radio contra harmonic mean labeling, rchmn (G), Order, Diameter, Smallest span

Exploration on human resource management and prediction model of data-driven information security in Internet of Things

The advent of the Internet of Things (IoT) has accelerated the pace of economic development across all sectors. However, it has also brought significant challenges to traditional human resource management, revealing an increasing number of problems and making it unable to meet the needs of contemporary enterprise management. The IoT has brought numerous conveniences to human society, but it has also led to security issues in communication networks. To ensure the security of these networks, it is necessary to integrate data-driven technologies to address this issue. In response to the current state of human resource management, this paper proposes the application of IoT technology in enterprise human resource management and combines it with radial basis function neural networks to construct a model for predicting enterprise human resource needs. The model was also experimentally analyzed. The results show that under this algorithm, the average prediction accuracy for the number of employees over five years is 90.2 %, and the average prediction accuracy for sales revenue is 93.9 %. These data indicate that the prediction accuracy of the model under this study's algorithm has significantly improved. This paper also conducted evaluation experiments on a wireless communication network security risk prediction model. The average prediction accuracy of four tests is 91.21 %, indicating that the model has high prediction accuracy. By introducing data-driven technology and IoT applications, this study provides new solutions for human resource management and communication network security, promoting technological innovation in the fields of traditional human resource management and information security management. The research not only improves the accuracy of the prediction models but also provides strong support for decision-making and risk management in related fields, demonstrating the great potential of big data and artificial intelligence technology in the future of enterprise management and security.

On the Physical Layer Security of Underwater Optical Wireless Communication Networks

On the Physical Layer Security of Underwater Optical Wireless Communication Networks

Role of Cybersecurity Legal Frameworks in Shaping the Risk Preparedness of the Telecommunication Sector in Safaricom Head Office, Nairobi, Kenya

The role of cybersecurity legal frameworks for assessing risk preparedness in the telecommunications industry is crucial to protecting sensitive information and guaranteeing the resilience of digital infrastructure. To investigate how legal frameworks affect the risk preparation tactics used by the massive telecom company, this research employs the Safaricom Head Office in Nairobi, Kenya, as a case study. The study adopts a descriptive methodology to thoroughly explore and describe the current cybersecurity legal landscape, including its conceptualization and subsequent impact on risk management within the company. This study is significant because of the rising reliance on digital technologies and the frequency and sophistication of cyber threats. Because the telecommunications sector is an essential backbone for many sectors, knowing the legal frameworks governing cybersecurity is critical to guaranteeing the reliability and security of communication networks. This includes determining how well Safaricom's cybersecurity policies correspond with regulatory requirements, identifying any gaps, and investigating compliance concerns. The study aims to gain a thorough understanding of the relationship between legal frameworks and risk management strategies, ultimately contributing to the improvement of cybersecurity practices in the telecommunications industry.

Integrating Unmanned Aerial Vehicles in Airspace: A Systematic Review

In this article, a comprehensive review of the integration of Unmanned Aerial Vehicles (UAVs) into shared airspace is presented. By applying a systematic review methodology, the study clarifies the main challenges, problems, and possible fixes related to safety, coordination, and regulatory frameworks. The results demonstrate the critical role that several elements play in supporting the safety of UAV integration. These elements include multi-layered airspace models, careful path planning, secure communication networks, Conflict Detection and Resolution (CDR) strategies, and strong regulations. The paper explores the potential of Human-in-the-loop Reinforcement Learning (HRL) and Reinforcement Learning (RL) algorithms to train UAVs for maneuvering through complex terrain and adapting to changing circumstances. The study's conclusions highlight the importance of ongoing research projects, stakeholder cooperation and continuous support for technology developments-all of which are necessary to ensure the safe and orderly integration of UAVs into airspace.

Using path coloring of graphs for communication in social networks

An L (p1, p2, p3, … , pm)- labeling of a graph G, has the vertices of G assigned with non-negative integers, such that the vertices at distance j should have at least pj as their label difference. If m = 3 and p1 = 3, p2 = 2, p3 = 1, it is called an L (3, 2, 1)-labeling which is widely studied in the literature. In this paper, we define an L (3, 2, 1)-path coloring of G as a labeling g : V (G) → Z+ such that between every pair of vertices there exists at least one path P where in the labeling restricted to this path is an L (3, 2, 1)-labeling. Among the labels assigned to any vertex of G under g, the maximum label is called the span of g. The L (3, 2, 1)-connection number of a graph G, denoted by k3c (G) is defined as the minimum value of span of g taken over all such labelings g. We call graphs with the special property that k3c (G) = |V (G) | as L (3, 2, 1)-path graceful. In this paper, we obtain k3c (G) of graphs that possess a Hamiltonian path and carry forward the discussion to certain classes of graphs which do not possess a Hamiltonian path, which is novel to this paper. Although different kinds of labeling are studied in the literature with different mathematical constraints imposed, the idea of showing the existence of a graph with a given number as its minimum labeling number has rarely been addressed. We show that given any positive integer, there always exists an L (3, 2, 1)-path graceful graph with the given integer as its k3c (G), thus addressing the inverse question. Finally exploiting the fact that there is no gap on the k3c (G) number line, we give an application of path colorings for secure communication on social networking sites. Efforts to deploy graph coloring in task scheduling, interference-free transmission, etc have been dealt by earlier researchers. In this paper, we deploy the L (3, 2, 1)-path coloring technique defined by us for secure communication in social networks, which has not been dealt with so far.