Network Security Requirements Research Articles

Challenges and Advances in Analyzing TLS 1.3-Encrypted Traffic: A Comprehensive Survey

The widespread adoption of encrypted communication protocols has significantly enhanced network security and user privacy, simultaneously elevating the importance of encrypted traffic analysis across various domains, including network anomaly detection. The Transport Layer Security (TLS) 1.3 protocol, introduced in 2018, has gained rapid popularity due to its enhanced security features and improved performance. However, TLS 1.3’s security enhancements, such as encrypting more of the handshake process, present unprecedented challenges for encrypted traffic analysis, rendering traditional methods designed for TLS 1.2 and earlier versions ineffective and necessitating the development of novel analytical techniques. This comprehensive survey provides a thorough review of the latest advancements in TLS 1.3 traffic analysis. First, we examine the impact of TLS 1.3’s new features, including Encrypted ClientHello (ECH), 0-RTT session resumption, and Perfect Forward Secrecy (PFS), on existing traffic analysis techniques. We then present a systematic overview of state-of-the-art methods for analyzing TLS 1.3 traffic, encompassing middlebox-based interception, searchable encryption, and machine learning-based approaches. For each method, we provide a critical analysis of its advantages, limitations, and applicable scenarios. Furthermore, we compile and review key datasets utilized in machine learning-based TLS 1.3 traffic analysis research. Finally, we discuss the main challenges and potential future research directions for TLS 1.3 traffic analysis. Given that TLS 1.3 is still in the early stages of widespread deployment, research in this field remains nascent. This survey aims to provide researchers and practitioners with a comprehensive reference, facilitating the development of more effective TLS 1.3 traffic analysis techniques that balance network security requirements with user privacy protection.

Research on the influence of accounting computerization and networking on E-commerce

This papers translated from an article written by a professor from the School of Management, Suzhou University of Science and Technology focuses on the influence and change of translation accounting computerization. First of all, describe the changes: describe the changes in the efficiency of accounting and the way it works, etc., and then explain the differences with the traditional accounting industry, where the progress. What needs to be improved. Then, explain the changes of internal audit and internal control under the condition of accounting computerization, including the use of what new methods, what data application, what new treatment of statements and so on. At the same time, in order to have a deeper understanding of these changes, this paper also cites examples of companies to demonstrate. Discuss the company's internal control and audit, etc.Finally, stating the emerging risks and how to deal with them. After translating and reading this article, I deeply understand what changes have taken place in traditional accounting under the computerization of accounting, such as the improvement of efficiency, the improvement of network security requirements, the change of personnel training methods and so on. Although accounting computerization can improve efficiency, it also increases risks, so it is necessary to improve the system, accounting software, training talents and so on. In short, the journey of accounting computerization is full of opportunities and challenges. We should fully grasp the opportunities and meet the challenges independently.

Secured Computation Offloading in Multi-Access Mobile Edge Computing Networks through Deep Reinforcement Learning

Mobile edge computing (MEC) has emerged as a pivotal technology to address the computational demands of resource-constrained mobile devices by offloading tasks to nearby edge servers. However, ensuring the security and efficiency of computation offloading in multiaccess MEC networks remains a critical challenge. This paper proposes a novel approach that leverages deep reinforcement learning (DRL) for secure computation offloading in multi-access MEC networks. The proposed framework utilizes DRL agents to dynamically make offloading decisions based on the current network conditions, resource availability, and security requirements. The agents learn optimal offloading policies through interactions with the environment, aiming to maximize task completion efficiency while minimizing security risks. To enhance security, the framework integrates encryption techniques and access control mechanisms to protect sensitive data during offloading. The proposed approach undergoes comprehensive simulations to assess its performance in terms of security, efficiency, and scalability. The results demonstrate that the DRL-based approach effectively balances the tradeoffs between security and efficiency, achieving robust and adaptive computation offloading in multi-access MEC networks. This study contributes to advancing the state-of-the-art in secure and efficient mobile edge computing systems, fostering the development of intelligent and resilient MEC solutions for future mobile networks.

Vehicular ad-hoc security improvements using decentralised consensus blockchain

For safer roads, a more efficient driving experience, and protection against attackers, the intelligent cars communicate with one another or with the roadside unit (RSU). The fundamental security requirements of Vehicular Ad-hoc Networks (VANETs) must be nonrepudiable, genuine, and incorporate these three. Additionally, protecting against attackers should be done in particular specific situations. However, the VANET's main disadvantages are its centralized design and the absence of procedures for ensuring confidentiality and privacy. In this paper, proposed decentralised consensus blockchain architecture for VANET that uses blockchain technology to address these problems. The VANET no longer needs a central authority or third-party administration thanks to the introduction of the blockchain. In order to ensure data integrity and accelerate up system processing, the hash value of the pseudonyms will be recorded on the blockchain. By eliminating trust difficulties between the entities, this effectively addresses challenges that arise in centralised designs. The suggested method for VANETs security. Experimental investigation demonstrates that the provided architecture outperforms the available options in terms of security enhancement.

AC-SDVN: An Access Control Protocol for Video Multicast in Software Defined Vehicular Networks

The way to use limited bandwidth resources to achieve high-quality video services in vehicular networks is an important research topic. A large number of studies have shown that the fast-growing field of software defined networking (SDN) can provide solutions to the problems encountered by traditional IP networks when implementing video multicasting. However, there is no research addressing the security issues for this scenario. In this paper, we explore the application scenarios of video multicast in software defined vehicular networks (SDVN), and propose a secure and effective access control protocol to solve multicast security issues. This protocol realizes the authentication of multicast video requesting vehicles and RSUs. According to the authentication results, the SDN controller constructs multicast paths that only reach legitimate RSUs and vehicles, and only the vehicle passing the authentication can obtain video decryption keys. The protocol resists common attacks and satisfies the security requirements in vehicular networks. In addition, the scheme supports batch verification, which reduces the time cost of authentication, and adopts broadcast encryption technology to effectively reduce the communication load. Compared with related schemes, our protocol performs better in terms of computation and communication cost, packet loss rate, and time delay.

AHP-Based Network Security Situation Assessment for Industrial Internet of Things

The Industrial Internet of Things (IIoT) is used in various industries to achieve industrial automation and intelligence. Therefore, it is important to assess the network security situation of the IIoT. The existing network situation assessment methods do not take into account the particularity of the IIoT’s network security requirements and cannot achieve accurate assessment. In addition, IIoT transmits a lot of heterogeneous data, which is subject to cyber attacks, and existing classification methods cannot effectively deal with unbalanced data. To solve the above problems, this paper first considers the special network security requirements of the IIoT, and proposes a quantitative evaluation method of network security based on the Analytic Hierarchy Process (AHP). Then, the average under-/oversampling (AUOS) method is proposed to solve the problem of unbalance of network attack data. Finally, an IIoT network security situation assessment classifier based on the eXtreme Gradient Boosting (XGBoost) is constructed. Experiments show that the situation assessment method proposed in this paper can more accurately characterize the network security state of the IIoT. The AUOS method can achieve data balance without generating too much data, and does not burden the training of the model. The classifier constructed in this paper is superior to the traditional classification algorithm.

Analysis of Network Security Countermeasures From the Perspective of Improved FS Algorithm and ICT Convergence

In this paper, the forward selection (FS) algorithm is introduced on the basis of information and communication technology, and the design of intrusion detection method for communication network is carried out. By studying the classification and detection pattern matching of communication network intrusion behavior, extracting the intrusion behavior features of communication network based on FS algorithm, and optimizing the intrusion detection and learning effect based on the limit learning machine, the intrusion behavior attributes of communication network are clarified, and a new detection method is proposed to solve the problems of low detection accuracy and low recall in the current intrusion behavior detection of complex communication network environments. Compared with the intrusion detection method based on GA-SVM algorithm, the accuracy of the detection results reaches 94.23%, and the recall rate exceeds 97%, which is obviously better than the 85% accuracy and 75% recall rate of the traditional detection method, which can ensure the security of the communication network environment. In addition, this paper proposes the APDR dynamic comprehensive information security assurance system model, which has considerable flexibility and can respond to current network security requirements.

A Survey on variants of DoS attacks: Issues and defense mechanisms

Wireless-based networks encompass assisted human life in distinct domains like Agriculture, health, infrastructure, climate, transportation and defense. In particular, the wireless sensor networks have been addressed in this article. Though it has many advancements, providing secure data transmission needs a major focus on these platforms. The disruptions or interference is one of the vulnerable security problems in Wireless Sensor Networks. Inside the network, an intruder can encroach and interrupt the whole transmission process. The involvement of an intruder in the device must be remembered in the network. WSN encompasses a wide geographical region and focus on rectification of issues in protocols for routing, interoperability, connectivity, and defense plays a major role. Hence, this article addresses about routing protocols of WSN, applications, recent network security issues and their variants of defense mechanisms. The conclusion depicts the classification of network security issues, requirements, and descriptive defense mechanisms for secure data transmission.

Network Slicing in 6G: An Authentication Framework for Unattended Terminals

Compared to the 5G network, the future 6G network is a multi-scenario application network containing more unattended terminals. The network slicing technology inherited from 5G enables more service providers to offer the same services with differentiated quality of services (QoS) and costs for their subscribers in 6G networks, in which more complex tasks occur for unattended terminals, such as unmanned factories, unmanned medical care, and unmanned rescues. However, network slice access of unattended terminals faces challenges. Specifically, physical attacks are a significant threat to unattended terminals in an open environment. The constrained resources and seamless services of unattended terminals also have to be considered. Unfortunately, there is currently a lack of an authentication scheme to address the above situation. As new lightweight hardware security primitive, Physical Unclonable Function (PUF) is an ideal solution to promote the security of unattended terminals. This article provides a specific authentication framework for unattended terminals in 6G-enabled network slices. Specifically, based on PUF, we first propose a physically secure slice access authentication protocol. Then we extend it to support fast inter-slice handover authentication, ensuring service continuity. Moreover, we prove the security of the proposed framework and conclude that it satisfies the higher security requirements of the 6G network. Finally, the performance evaluation with three other state-of-the-art authentication schemes demonstrates the superior efficiency of the proposed framework.

Few-Shot Learning-Based Network Intrusion Detection through an Enhanced Parallelized Triplet Network

Network intrusion detection is one of the critical techniques to enhance cybersecurity. Several few-shot learning-based methods have recently been proposed to alleviate the dependence on large training samples in many supervised learning methods. However, it is still a challenge to achieve real-time higher-accuracy intrusion detection which is an essential requirement for high-speed network security. In this study, we propose a novel few-shot learning-based network intrusion detection method to address this challenge. Specifically, we improve the detection accuracy and real-time processing speed simultaneously in the metric procedure via two mechanisms: (i) we utilize a hard sample selection scheme as a refining stage of our triplet network model training to increase the detection accuracy; and (ii) we design a lightweight embedding network and parallelize the metric feature extraction process to achieve real-time analysis speed. To evaluate the proposed method, we construct few-shot learning-based datasets by using two real and heterogeneous network traffic intrusion detection data sources. Extensive results demonstrate that our method outperforms the state-of-the-art methods in terms of real-time performance and high detection accuracy of malicious samples.

TADR-EAODV: A trust-aware dynamic routing algorithm based on extended AODV protocol for secure communications in wireless sensor networks

Compliance with security requirements in Wireless Sensor Networks (WSNs) is known as an important phenomenon in conserving energy consumption due to its dynamic topology. Energy consumption management in WSN can be achieved through secure routing protocols. Authentication, firewall and intrusion detection, and trust management are common ways to provide security on the WSNs. Meanwhile, trust management provides better performance due to ensuring distributed security through collaboration. In this paper, a Trust-Aware Dynamic Routing algorithm based on Extended AODV protocol for secure communications in the WSN (TADR-EAODV) is proposed. TADR-EAODV considers factors such as direct trust, recommended trust, connectivity strength, energy rate and worthiness score to measure the distributed safety level of nodes in routing. We use the AODV protocol for routing work, which is extended through a multi-route routing approach. In addition, a centralized ensemble clustering for node grouping is included in TADR-EAODV, which enables clustering-based routing to enhance WSN performance. Extensive experiments have been performed in the presence of denial-of-service attacks to verify our claims. The experimental results prove that high-performance TADR-EAODV has been able to identify attackers by detecting their anomalous behavior. Besides, TADR-EAODV has improved the average packet transfer rate by 6% to 17% compared to existing state-of-the-art algorithms such as LEACH-TM, TAAO-SDTIM and TAOSC-MHR.

A UAV swarm communication network architecture based on consortium blockchain

In the context of the development of UAVs towards clustering, intelligence, and autonomy, it is necessary to ensure that multiple UAVs and ground control stations can communicate and share information securely in real-time so that UAV swarms can make real-time and effective decisions and collaborations. These factors pose challenges to the security, robustness, and operational efficiency of UAV swarm communication networks. This paper combines blockchain technology with a UAV swarm communication network, proposes a new UAV swarm communication network architecture based on consortium blockchain, and describes the network structure and transaction process in detail. The performance analysis shows that the security mechanism of the architecture can meet the security requirements of the UAV swarm communication network. And this solution is superior to existing solutions based on blockchain technology such as Ethereum in performance and is a technical solution with both security and usability.

Open source SIEM solutions for an enterprise

PurposeThe security of applications, systems and networks has always been the source of great concern for both enterprises and common users. Different security tools like intrusion detection system/intrusion prevention system and firewalls are available that provide preventive security to the enterprise networks. However, security information and event management (SIEM) systems use these tools in combination to collect events from diverse data sources across the network. SIEM is a proactive tool that processes the events to present a unified security view of the whole network at one location. SIEM system has, therefore, become an essential component of an enterprise network security architecture. However, from various options available, the selection of a suitable and cost-effective open source SIEM solution that can effectively meet most of the security requirements of small-to-medium-sized enterprises (SMEs) is not simple because of the lack of strong analysis.Design/methodology/approachIn this work, the authors first review the security challenges faced by different SME sectors and then consider a comprehensive comparative analysis of the capabilities of well-known open source SIEM solutions. Based on this, the authors provide requirements based recommendations of open source SIEM solutions for SMEs. This paper aims to provide a valuable resource that can be referred to by SMEs for the selection of a SIEM system best suited to their organization’s security posture.FindingsSecurity requirements of SMEs vary according to their network infrastructure; therefore, every open source SIEM solution would not be suitable for an SME. Selection of a SIEM solution from available open source solutions based upon the security requirements of an SME network is a critical task. Therefore, in this work, a meaningful insight for the selection of an appropriate SIEM solution for SMEs is provided.Originality/valueMajor contribution of this work is the mapping of the security requirements of the SME sectors under consideration, against the open source SIEM options to provide meaningful insight for SMEs in the selection of an appropriate solution.

A Survey on Zero Trust Architecture: Challenges and Future Trends

The traditional perimeter-based network protection model cannot adapt to the development of current technology. Zero trust is a new type of network security model, which is based on the concept of never trust and always verify. Whether the access subject is in the internal network or the external network, it needs to be authenticated to access resources. The zero trust model has received extensive attention in research and practice because it can meet the new network security requirements. However, the application of zero trust is still in its infancy, and enterprises, organizations, and individuals are not fully aware of the advantages and disadvantages of zero trust, which greatly hinders the application of zero trust. This paper introduces the existing zero trust architecture and analyzes the core technologies including identity authentication, access control, and trust assessment, which are mainly relied on in the zero trust architecture. The main solutions under each technology are compared and analyzed to summarize the advantages and disadvantages, as well as the current challenges and future research trends. Our goal is to provide support for the research and application of future zero trust architectures.

Trusted authority based session key agreement and authentication algorithm for smart grid networks

AbstractThe information exchanged over the smart grid networks is sensitive and private. As such, proper mechanisms must be put in place to protect these messages from security and privacy violations. Although many schemes have been presented in literature to address these challenges, a number of them rarely consider concurrent authentication of smart meters, while some are inefficient or still lack some of the smart grid network security and privacy requirements. In this article, a novel concurrent smart meters authentication algorithm is presented, based on some trusted authority. Formal security analysis of this algorithm is executed using Burrows‐Abadi‐Needham logic, which shows that this algorithm provides strong authentication among the smart meter, utility service provider and trusted authority. In addition, session keys are independently computed and verified between the smart meter and utility service provider with the help of the trusted authority. Informal security analysis shows that this algorithm provides device anonymity, perfect forward key secrecy, strong mutual authentication and is resilient against replay, de‐synchronization, privileged insider, impersonation, eavesdropping, side‐channel, and traceability attacks. In terms of performance, the proposed algorithm exhibits the least communication and computation overheads when compared with other related schemes.

LBVP: A Lightweight Batch Verification Protocol for Fog-Based Vehicular Networks Using Self-Certified Public Key Cryptography

To achieve efficient vehicular network communication and service, researchers proposed fog-based vehicular networks (FVNs). One of the prerequisites for developing large-scale FVNs is ensuring the security and privacy of the entire network environment. However, the existing schemes proposed for FVNs exist considerable calculation and communication costs and/or security vulnerabilities. Therefore, to promote efficient FVN authentication, we propose a lightweight security protocol using self-certified public key cryptography. In the protocol, the trusted authority does not need to participate in the authentication process between the vehicle and the fog node online. And the vehicle can dynamically update its login password and pseudonym, without performing complicated interactive steps with the trusted authority. In addition, our protocol supports batch verification, which significantly improves the system authentication efficiency. A detailed security analysis reveals that our protocol can meet the security requirements of vehicular networks while resisting the common types of attack. Calculation and communication overhead comparisons further prove that our protocol exhibits better performance than related schemes.

IoT Security on Smart Grid: Threats and Mitigation Frameworks

The number of smart grid IoTs is expected to grow exponentially in the near future, as predicted by the analyst. The improvement of a smart grid IoT security system increases due to communication technologies used in traditional power systems. Smart grid IoTs include critical devices due to its complex architectures. Smart grid IoTs that are connected and controlled remotely through the internet are becoming more universal. As a result, homes and businesses have ever increasing attack surfaces on their networks. It can lead to security arrears, and large-scale economic damage when the confidentiality and integrity of the communication is broken down. These huge systems may be endangered to threats. Consequently, there is a lot of research effort to enhance smart grid security in government, industry, and academia. We present a broad survey supported by a thorough review of earlier work. Moreover, recent advances and corrective measures are presented on smart grid IoT security. In this paper, the threats and mitigation framework of the smart grid IoT are analyzed. This paper reviews the existing literature on the smart grid IoTs in energy systems. We focus on threat types and provide an in-depth discussion of the threat state of the smart grid. Explicitly, we focus on the discussion and scrutiny of network vulnerabilities, attack countermeasures, and security requirements. We focus to supply a deep understanding of threat vulnerabilities and mitigation framework and give a path on future research directions for threat in smart grid IoTs.

Analysis Model of Spoken English Evaluation Algorithm Based on Intelligent Algorithm of Internet of Things.

With the in-depth promotion of the national strategy for the integration of artificial intelligence technology and entity development, speech recognition processing technology, as an important medium of human-computer interaction, has received extensive attention and motivated research in industry and academia. However, the existing accurate speech recognition products are based on massive data platform, which has the problems of slow response and security risk, which makes it difficult for the existing speech recognition products to meet the application requirements for timely translation of speech with high response time and network security requirements under the condition of network instability and insecurity. Based on this, this paper studies the analysis model of oral English evaluation algorithm based on Internet of things intelligent algorithm in speech recognition technology. Firstly, based on the automatic machine learning and lightweight learning strategy, a lightweight technology of automatic speech recognition depth neural network adapted to the edge computing power is proposed. Secondly, the quantitative evaluation of Internet of things intelligent classification algorithm and big data analysis in this system is described. In the evaluation, the evaluation method of oral English characteristics is adopted. At the same time, the Internet of things intelligent classification algorithm and big data analysis strategy are used to evaluate the accuracy of oral English. Finally, the experimental results show that the oral English feature recognition system based on Internet of things intelligent classification algorithm and big data analysis has the advantages of good reliability, high intelligence, and strong ability to resist subjective factors, which proves the advantages of Internet of things intelligent classification algorithm and big data analysis in English feature recognition.

Guest editorial: Smart communications and networking: architecture, applications, and future challenges

Guest editorial: Smart communications and networking: architecture, applications, and future challenges

Role of Digital Watermarking in Wireless Sensor Network

Abstract: WSN has been exhilarated in many application areas such as military, medical, environment, etc. Due to the rapid increase in applications, it causes proportionality to security threats. Mostly, nodes used, are independent of human reach and dependent on their limited resources, the major challenges can be framed as energy consumption and resource reliability. Introduction: Due to the limitation of resources in the sensor nodes, the traditionally intensive security mechanism is not feasible for WSNs. This limitation brought the concept of Digital watermarking in existence. The intent of this paper is to investigate the security related issues and role of watermarking in wireless sensor networks. Watermarking is an effective way to provide security, integrity, data aggregation and robustness in WSN. Mehtod: Digital watermarking is essential in WSN since it provides security in various forms such as confidentiality, service availability and data freshness. We have briefly discussed the various security requirements in the wireless sensor networks. Several issues and challenges, as well as the various threats of WMSN, is also considered. The related work, suggests that lots of research work are required to improve the security and authentication issues of WMSN by digital watermarking. This survey contribution will be helpful for researcher to accomplish effective watermarking scheme for WSN. Result: WSN is the collection of sensors that are spread in the environment. They measure and monitor physical conditions like temperature, sound, pressure, humidity, etc. and organize the collected data at the main location. The base station then forwards the data to end-users who analyze and make strategic decisions. Nowadays the modern network is bi-directional i.e. we can control the activity of the sensor. The central stations, unlike another sensor network, have infinite power, plenty of memory, powerful processors and a high bandwidth link. Whereas sensors are small in size, have fewer computation abilities, transfer wirelessly and are power-driven by small batteries Conclusion: Watermarking is an effective way to provide security, integrity, data aggregation and robustness in WSN. Digital watermarking is essential in WSN since it provides security in various forms such as confidentiality, data integrity, service availability and data freshness. In this paper, we have briefly discussed the various security requirements in the wireless sensor networks. We have also discussed work done by several authors in WSN with watermarking techniques Discussion: Wireless network faces more challenges as compared to wired network. In WSN, maximum amount of data and information can be stealed and effortlessly accessed during transmission. The nodes in a wireless sensor network (WSN) are resources constrained. Due to which WSNs have certain challenges i.e. processing power, storage and computational capacity and high bandwidth demand. Security schemes are not easy to design since the network tends to be large and ad-hoc. The analysis for privacy and security have been explored by some authors like J. Zhu et al. In recent years, a cryptography-based security designs have been proposed for WSNs. Cryptography is the process of concealing the information into the cipher text by encrypting it.