Recent Advances and Applications of Network Security and Cryptography

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 June 2024) | Viewed by 12711

Special Issue Editor


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Guest Editor
School of Cyber Engineering, Xidian University, Xi’an 710071, China
Interests: cryptography; machine learning in cyber security; Internet of Things security

Special Issue Information

Dear Colleagues,

With the rapid growth of the Internet, network security has become an inevitable challenge for any organization whose internal private systems are connected to the Internet. The paradigm shift to variable interconnection topologies in network environments introduced challenges to traditional network security approaches. Various types of attacks and threats pose ongoing challenges, such as malware, distributed denial of service attacks, man-in-the-middle (MitM) attacks, and identity and access management attacks. The flexibility in interconnections makes systems susceptible to various attacks from eavesdroppers. These attacks and threats underscore the complexity of network security, prompting organizations and individuals to implement multi-layered security measures, including firewalls, intrusion detection systems, encrypted communication, regular updates, and vulnerability management.

One of the primary concerns addressed in network security is the security and privacy of the huge amount of communicated information, implying that network security measures encompass a range of strategies, protocols, and technologies aimed at preventing unauthorized access, interception, or compromise of the communicated information.  The multifaceted nature of network security measures is crucial for maintaining the integrity of information exchanges. Moreover, the advancement of mobile technologies and the Internet of Things (IoT) has prompted the development of now-existing cryptographic and security measures that can be adapted and optimized to address the security implications of these innovations. This adaptation was necessary to accommodate the limited resources of devices, including battery power, storage, and processing capabilities.

In the context of these challenges and advancements, this Special Issue aims to shed light on recent breakthroughs and applications within the dynamic fields of network security and cryptography.  It seeks to delve into cutting-edge developments, innovative approaches, and emerging technologies that contribute to enhancing the security of networks and the robustness of cryptographic systems. The scope includes advancements in encryption algorithms, secure communication protocols, threat detection mechanisms, machine learning applications in security, blockchain cryptography, and the evolving challenges and solutions in network security. Solicited papers include those on the following topics, among others:

  • Advanced cryptographic techniques
  • Secure communication protocols
  • Cryptographic calculations
  • Web security
  • System security
  • Mobile security and IoT security
  • Machine learning and AI for cybersecurity
  • Security in cloud and distributed computing
  • Cybersecurity of communication technologies
  • Threat detection
  • Network security application
  • Blockchain technologies
  • Privacy-preserving technologies
  • N attacks and defenses of machine learning
  • Topological vulnerabilities of GNNs.

Prof. Dr. Zhuo Ma
Guest Editor

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Keywords

  • network security
  • cryptography
  • privacy preservations

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Published Papers (9 papers)

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Research

17 pages, 732 KiB  
Article
SMWE: A Framework for Secure and Makespan-Oriented Workflow Execution in Serverless Computing
by Hao Liang, Shuai Zhang, Xinlei Liu, Guozhen Cheng, Hailong Ma and Qingfeng Wang
Electronics 2024, 13(16), 3246; https://doi.org/10.3390/electronics13163246 - 15 Aug 2024
Viewed by 1075
Abstract
Serverless computing is a promising paradigm that greatly simplifies cloud programming. With serverless computing, developers simply provide event-driven functions to a serverless platform, and these functions can be orchestrated as serverless workflows to accomplish complex tasks. Due to the lightweight limitation of functions, [...] Read more.
Serverless computing is a promising paradigm that greatly simplifies cloud programming. With serverless computing, developers simply provide event-driven functions to a serverless platform, and these functions can be orchestrated as serverless workflows to accomplish complex tasks. Due to the lightweight limitation of functions, serverless workflows not only suffer from existing vulnerability-based threats but also face new security threats from the function compiling phase. In this paper, we present SMWE, a secure and makespan-oriented workflow execution framework in serverless computing. SMWE enables all life cycle protection for functions by adopting compiler shifting and running environment replacement in the serverless workflow. Furthermore, SMWE balances the tradeoff between security and makespan by carefully scheduling functions to running environments and selectively applying the secure techniques to functions. Extensive evaluations show that SMWE significantly increases the security of serverless workflows with small makespan cost. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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19 pages, 4527 KiB  
Article
Ensuring Cross-Chain Transmission Technique Utilizing TPM and Establishing Cross-Trusted Root Security via SM Algorithm
by Yichuan Wang, Yiliang Yan, Yaling Zhang, Mengjie Tian and Xiaoxue Liu
Electronics 2024, 13(15), 2978; https://doi.org/10.3390/electronics13152978 - 28 Jul 2024
Viewed by 1001
Abstract
As blockchain technology advances, cross-chain interoperability has become a crucial requirement for achieving seamless interaction among multiple chains. To solve this problem, this paper proposes a scholarly approach to the development of a cross-chain-secure transmission technique, incorporating the Trusted Platform Module (TPM) and [...] Read more.
As blockchain technology advances, cross-chain interoperability has become a crucial requirement for achieving seamless interaction among multiple chains. To solve this problem, this paper proposes a scholarly approach to the development of a cross-chain-secure transmission technique, incorporating the Trusted Platform Module (TPM) and the SM algorithm, which is based on trusted roots. This research paper elaborates on the design and implementation of the cross-chain-secure transmission technique based on TPM and the SM algorithm, emphasizing the academic rigor necessary for addressing the security requirements of cross-chain interactions. The research shows that compared with the previous method, the throughput of production capacity is not significantly different from that before and after adding the network delay, and the success rate of preventing attacks is increased by 46.9% by simulating related attacks. After multiple rounds of experiments, the effectiveness and feasibility of this technology in protecting cross-chain communication data are verified. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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17 pages, 441 KiB  
Article
A Zero-Knowledge-Proof-Based Anonymous and Revocable Scheme for Cross-Domain Authentication
by Xinjian Zhao, Fei Xia, Hanning Xia, Yunlong Mao and Shi Chen
Electronics 2024, 13(14), 2730; https://doi.org/10.3390/electronics13142730 - 11 Jul 2024
Viewed by 1291
Abstract
Authentication is a crucial security service on the Internet. In real-world applications, multiple independent trust domains often exist, with each recognizing only certain identities within their own systems. During cross-domain access, users cannot directly use their original certificates, which presents a cross-domain authentication [...] Read more.
Authentication is a crucial security service on the Internet. In real-world applications, multiple independent trust domains often exist, with each recognizing only certain identities within their own systems. During cross-domain access, users cannot directly use their original certificates, which presents a cross-domain authentication problem. Traditional centralized schemes typically employ a trusted third party (TTP) to facilitate the transfer of identity trust across domains. These schemes inevitably inherit the vulnerabilities associated with single points of failure. In contrast, blockchain-based decentralized schemes effectively eliminate the potential threats posed by TTPs. However, the openness and transparency of the blockchain also bring new security issues, such as privacy leakage. In this paper, we propose a zk-SNARK-based anonymous scheme on the blockchain for cross-domain authentication. Specifically, our scheme adopts an authorization-then-proof structure, which strikes a delicate balance between anonymity and revocability. We provide theoretical proofs for the security of our scheme and explain how it achieves proactive revocability. Experimental evaluation results demonstrated that our scheme is both secure and efficient, and the revocation could be accomplished by introducing only 64 bytes of on-chain storage with one hash comparison. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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17 pages, 4200 KiB  
Article
A Browser Fingerprint Authentication Scheme Based on the Browser Cache Side-Channel Technology
by Yiming Yan, Haiyong Zhao and Haipeng Qu
Electronics 2024, 13(14), 2728; https://doi.org/10.3390/electronics13142728 - 11 Jul 2024
Viewed by 1111
Abstract
Users encounter various threats, such as cross-site scripting attacks and session hijacking, when they perform login operations in the browser. These attacks pose significant risks to the integrity and confidentiality of personal data. The browser fingerprint, as an authentication technique, can effectively enhance [...] Read more.
Users encounter various threats, such as cross-site scripting attacks and session hijacking, when they perform login operations in the browser. These attacks pose significant risks to the integrity and confidentiality of personal data. The browser fingerprint, as an authentication technique, can effectively enhance user security. However, attackers can bypass browser fingerprint authentication through phishing attacks and other methods, leading to unauthorized logins. To address these issues, we propose a secure browser fingerprint authentication scheme that integrates the data of the browser cache side-channel into the traditional browser fingerprint. Consequently, it enhances the dynamics and non-determinism of the browser fingerprint and improves the anti-attack capabilities of the authentication process. Experimental results demonstrate that this scheme can effectively mitigate phishing attacks and man-in-the-middle attacks, achieving a 95.33% recognition rate for attackers and a 96.17% recall rate for authorized users. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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16 pages, 1201 KiB  
Article
Graph Transformer Network Incorporating Sparse Representation for Multivariate Time Series Anomaly Detection
by Qian Yang, Jiaming Zhang, Junjie Zhang, Cailing Sun, Shanyi Xie, Shangdong Liu and Yimu Ji
Electronics 2024, 13(11), 2032; https://doi.org/10.3390/electronics13112032 - 23 May 2024
Viewed by 1643
Abstract
Cyber–physical systems (CPSs) serve as the pivotal core of Internet of Things (IoT) infrastructures, such as smart grids and intelligent transportation, deploying interconnected sensing devices to monitor operating status. With increasing decentralization, the surge in sensor devices expands the potential vulnerability to cyber [...] Read more.
Cyber–physical systems (CPSs) serve as the pivotal core of Internet of Things (IoT) infrastructures, such as smart grids and intelligent transportation, deploying interconnected sensing devices to monitor operating status. With increasing decentralization, the surge in sensor devices expands the potential vulnerability to cyber attacks. It is imperative to conduct anomaly detection research on the multivariate time series data that these sensors produce to bolster the security of distributed CPSs. However, the high dimensionality, absence of anomaly labels in real-world datasets, and intricate non-linear relationships among sensors present considerable challenges in formulating effective anomaly detection algorithms. Recent deep-learning methods have achieved progress in the field of anomaly detection. Yet, many methods either rely on statistical models that struggle to capture non-linear relationships or use conventional deep learning models like CNN and LSTM, which do not explicitly learn inter-variable correlations. In this study, we propose a novel unsupervised anomaly detection method that integrates Sparse Autoencoder with Graph Transformer network (SGTrans). SGTrans leverages Sparse Autoencoder for the dimensionality reduction and reconstruction of high-dimensional time series, thus extracting meaningful hidden representations. Then, the multivariate time series are mapped into a graph structure. We introduce a multi-head attention mechanism from Transformer into graph structure learning, constructing a Graph Transformer network forecasting module. This module performs attentive information propagation between long-distance sensor nodes and explicitly models the complex temporal dependencies among them to enhance the prediction of future behaviors. Extensive experiments and evaluations on three publicly available real-world datasets demonstrate the effectiveness of our approach. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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10 pages, 2493 KiB  
Article
Progressive Reconstruction on Region-Based Secret Image Sharing
by Yanxiao Liu, Qindong Sun, Zhihai Yang, Yongluan Zhou, Weihua Zhao and Dantong Shi
Electronics 2024, 13(8), 1529; https://doi.org/10.3390/electronics13081529 - 17 Apr 2024
Viewed by 1187
Abstract
(k,n) threshold progressive secret image sharing (PSIS) has become an important issue in recent years. In (k,n) PSIS, a secret image is encrypted into n shadows such that k to n shadows can gradually reconstruct [...] Read more.
(k,n) threshold progressive secret image sharing (PSIS) has become an important issue in recent years. In (k,n) PSIS, a secret image is encrypted into n shadows such that k to n shadows can gradually reconstruct the secret image. Since an image can usually be divided into different regions in such a way that each region includes information with different importance levels, region-based PSIS has also been proposed where the reconstruction of different regions requires different thresholds on the shadow numbers. In this work, we propose new region-based (k,n) PSIS that achieves a novel reconstruction model, where all regions possess the property of (k,n) threshold progressive reconstruction, but the same number of shadows recovers a lower proportion of information in regions with a higher importance level. This new reconstruction model can further complete the application of region-based PSIS, where each region has an equal minimum threshold for reconstruction, and the difference in importance levels between regions can be reflected in the proportion of the recovered image using the same number of shadows. A theoretical analysis proves the correctness of the proposed scheme, and the experimental results from four secret images also show the practicality and effectiveness of the proposed scheme. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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23 pages, 2266 KiB  
Article
CrptAC: Find the Attack Chain with Multiple Encrypted System Logs
by Weiguo Lin, Jianfeng Ma, Teng Li, Haoyu Ye, Jiawei Zhang and Yongcai Xiao
Electronics 2024, 13(7), 1378; https://doi.org/10.3390/electronics13071378 - 5 Apr 2024
Viewed by 1121
Abstract
Clandestine assailants infiltrate intelligent systems in smart cities and homes for different purposes. These attacks leave clues behind in multiple logs. Systems usually upload their local syslogs as encrypted files to the cloud for longterm storage and resource saving. Therefore, the identification of [...] Read more.
Clandestine assailants infiltrate intelligent systems in smart cities and homes for different purposes. These attacks leave clues behind in multiple logs. Systems usually upload their local syslogs as encrypted files to the cloud for longterm storage and resource saving. Therefore, the identification of pre-attack steps through log investigation is crucial for proactive system protection. Current methodologies involve system diagnosis using logs, often relying on datasets for feature training. Furthermore, the prevalence of mass encrypted logs in the cloud introduces a new layer of complexity to this domain. To tackle these challenges, we introduce CrptAC, a system for Multiple Encrypted Log Correlated Analysis, aimed at reconstructing attack chains to prevent further attacks securely. CrptAC initiates by searching and downloading relevant log files from encrypted logs stored in an untrusted cloud environment. Utilizing the obtained logs, it addresses the challenge of discovering event relationships to establish the attack provenance. The system employs various logs to construct event sequences leading up to an attack. Subsequently, we utilize Weighted Graphs and the Longest Common Subsequences algorithm to identify regular steps preceding an attack without the need for third-party training datasets. This approach enables the proactive identification of pre-attack steps by analyzing related log sequences. We apply our methodology to predict attacks in cloud computing and router breach provenance environments. Finally, we validate the proposed method, demonstrating its effectiveness in constructing attack steps and conclusively identifying corresponding syslogs. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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12 pages, 602 KiB  
Article
Entropy Model of Rosin Autonomous Boolean Network Digital True Random Number Generator
by Yi Zong, Lihua Dong and Xiaoxin Lu
Electronics 2024, 13(6), 1140; https://doi.org/10.3390/electronics13061140 - 20 Mar 2024
Cited by 1 | Viewed by 972
Abstract
A True Random Number Generator (TRNG) is an important component in cryptographic algorithms and protocols. The Rosin Autonomous Boolean Network (ABN) digital TRNG has been widely studied due to its nice properties, such as low energy consumption, high speed, strong platform portability, and [...] Read more.
A True Random Number Generator (TRNG) is an important component in cryptographic algorithms and protocols. The Rosin Autonomous Boolean Network (ABN) digital TRNG has been widely studied due to its nice properties, such as low energy consumption, high speed, strong platform portability, and strong randomness. However, there is still a lack of suitable entropy models to deduce the requirement of design parameters to ensure true randomness. The current model to evaluate the entropy of oscillator-based TRNGs is not applicable for Rosin ABN TRNGs due to low-frequency noise. This work presents a new, suitable stochastic model to evaluate the entropy of Rosin ABN TRNGs. Theoretical analysis and simulation experiments verify the correctness and the effectiveness of the model, and, finally, the appropriate sampling parameters for Rosin ABN TRNGs are given for sufficient entropy per random bit to ensure true randomness. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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21 pages, 669 KiB  
Article
An ECC-Based Authentication Protocol for Dynamic Charging System of Electric Vehicles
by Jie Wang, Shengbao Wang, Kang Wen, Bosen Weng, Xin Zhou and Kefei Chen
Electronics 2024, 13(6), 1109; https://doi.org/10.3390/electronics13061109 - 18 Mar 2024
Cited by 1 | Viewed by 1377
Abstract
Dynamic wireless charging emerges as a promising technology, effectively alleviating range anxiety for electric vehicles in transit. However, the communication between the system’s various components, conducted over public channels, raises concerns about vulnerability to network attacks and message manipulation. Addressing data security and [...] Read more.
Dynamic wireless charging emerges as a promising technology, effectively alleviating range anxiety for electric vehicles in transit. However, the communication between the system’s various components, conducted over public channels, raises concerns about vulnerability to network attacks and message manipulation. Addressing data security and privacy protection in dynamic charging systems thus becomes a critical challenge. In this article, we present an authentication protocol tailored for dynamic charging systems. This protocol ensures secure and efficient authentication between vehicles and roadside devices without the help of a trusted center. We utilize a physical unclonable function (PUF) to resist physical capture attacks and employ the elliptic curve discrete logarithm problem (ECDLP) to provide forward security protection for session keys. We validated the security of our proposed scheme through comprehensive informal analyses, and formal security analysis using the ROR model and formal analysis tool ProVerif. Furthermore, comparative assessments reveal that our scheme outperforms other relevant protocols in terms of efficiency and security. Full article
(This article belongs to the Special Issue Recent Advances and Applications of Network Security and Cryptography)
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