High-Confidence Computing最新文献

英文中文

Erratum to “Exploring Personalized Internet of Things (PIoT), social connectivity, and Artificial Social Intelligence (ASI): A survey” [High-Confidence Computing 4 (2024) 100242]

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-12-01 DOI: 10.1016/j.hcc.2024.100294

Bisma Gulzar , Shabir Ahmad Sofi , Sahil Sholla

引用次数: 0

Identity-based threshold (multi) signature with private accountability for privacy-preserving blockchain 基于身份的阈值（多重）签名与隐私保护区块链的私人问责制

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-09-12 DOI: 10.1016/j.hcc.2024.100271

Jing Tian , Yanqi Zhao , Xiaoyi Yang , Xuan Zhao , Ruonan Chen , Yong Yu

Identity-based threshold signature (IDTHS) allows a threshold number of signers to generate signatures to improve the deterministic wallet in the blockchain. However, the IDTHS scheme cannot determine the identity of malicious signers in case of misinformation. To solve this challenge, we propose an identity-based threshold (multi) signature with private accountability (for short AIDTHS) for privacy-preserving blockchain. From the public perspective, AIDTHS is completely private and no user knows who participated in generating the signature. At the same time, when there is a problem with the transaction, a trace entity can trace and be accountable to the signers. We formally define the syntax and security model of AIDTHS. To address the issue of identifying malicious signers, we improve upon traditional identity-based threshold signatures by incorporating zero-knowledge proofs as part of the signature and leveraging a tracer holding tracing keys to identify all signers. Additionally, to protect the privacy of signers, the signature is no longer achievable by anyone, which requires a combiner holding the keys to produce a valid signature. We give a concrete construction of AIDTHS and prove its security. Finally, we implement the AIDTHS scheme and compare it with existing schemes. The key distribution algorithm of AIDTHS takes 34.60

μ s

and the signature algorithm takes 13.04 ms. The verification algorithm takes 1

s

, which is one-third of the time the TAPS scheme uses.

基于身份的阈值签名（IDTHS）允许一个阈值数量的签名者生成签名，以提高区块链中钱包的确定性。然而，IDTHS 方案在出现错误信息时无法确定恶意签名者的身份。为解决这一难题，我们为保护隐私的区块链提出了一种基于身份的阈值（多）签名与私人问责制（简称 AIDTHS）。从公众的角度来看，AIDTHS 是完全私有的，没有用户知道谁参与了签名的生成。同时，当交易出现问题时，跟踪实体可以对签名者进行跟踪和问责。我们正式定义了 AIDTHS 的语法和安全模型。为了解决识别恶意签名者的问题，我们改进了传统的基于身份的阈值签名，将零知识证明作为签名的一部分，并利用持有追踪密钥的追踪者来识别所有签名者。此外，为了保护签名者的隐私，签名不再是任何人都能实现的，这就需要一个持有密钥的组合器来生成有效的签名。我们给出了 AIDTHS 的具体结构，并证明了它的安全性。最后，我们实现了 AIDTHS 方案，并将其与现有方案进行了比较。AIDTHS 的密钥分配算法耗时 34.60 μs，签名算法耗时 13.04 ms。验证算法耗时 1 秒，是 TAPS 方案耗时的三分之一。

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引用次数: 0

Navigating the Digital Twin Network landscape: A survey on architecture, applications, privacy and security 数字孪生网络景观导航：架构、应用、隐私和安全调查

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-09-11 DOI: 10.1016/j.hcc.2024.100269

Akshita Maradapu Vera Venkata Sai , Chenyu Wang , Zhipeng Cai , Yingshu Li

In recent years, immense developments have occurred in the field of Artificial Intelligence (AI) and the spread of broadband and ubiquitous connectivity technologies. This has led to the development and commercialization of Digital Twin (DT) technology. The widespread adoption of DT has resulted in a new network paradigm called Digital Twin Networks (DTNs), which orchestrate through the networks of ubiquitous DTs and their corresponding physical assets. DTNs create virtual twins of physical objects via DT technology and realize the co-evolution between physical and virtual spaces through data processing, computing, and DT modeling. The high volume of user data and the ubiquitous communication systems in DTNs come with their own set of challenges. The most serious issue here is with respect to user data privacy and security because users of most applications are unaware of the data that they are sharing with these platforms and are naive in understanding the implications of the data breaches. Also, currently, there is not enough literature that focuses on privacy and security issues in DTN applications. In this survey, we first provide a clear idea of the components of DTNs and the common metrics used in literature to assess their performance. Next, we offer a standard network model that applies to most DTN applications to provide a better understanding of DTN’s complex and interleaved communications and the respective components. We then shed light on the common applications where DTNs have been adapted heavily and the privacy and security issues arising from the DTNs. We also provide different privacy and security countermeasures to address the previously mentioned issues in DTNs and list some state-of-the-art tools to mitigate the issues. Finally, we provide some open research issues and problems in the field of DTN privacy and security.

近年来，人工智能（AI）领域取得了巨大发展，宽带和无处不在的连接技术也在不断普及。这导致了数字孪生（DT）技术的发展和商业化。数字孪生技术的广泛应用产生了一种新的网络范式，即数字孪生网络（DTN），它通过无处不在的数字孪生网络及其相应的物理资产进行协调。DTN 通过 DT 技术创建物理对象的虚拟双胞胎，并通过数据处理、计算和 DT 建模实现物理空间和虚拟空间的共同演化。DTN 中的大量用户数据和无处不在的通信系统也带来了一系列挑战。其中最严重的问题是用户数据隐私和安全，因为大多数应用的用户并不知道他们正在与这些平台共享数据，而且对数据泄露的影响也缺乏足够的认识。此外，目前关注 DTN 应用中隐私和安全问题的文献还不够多。在本调查报告中，我们首先清楚地介绍了 DTN 的组成部分以及文献中用于评估其性能的常用指标。接下来，我们提供了一个适用于大多数 DTN 应用的标准网络模型，以便更好地理解 DTN 复杂而交错的通信和各自的组件。然后，我们阐明了 DTN 被大量采用的常见应用，以及 DTN 带来的隐私和安全问题。我们还提供了不同的隐私和安全对策来解决前面提到的 DTN 问题，并列出了一些最先进的工具来缓解这些问题。最后，我们提出了 DTN 隐私和安全领域的一些开放研究课题和问题。

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引用次数: 0

Erratum to “An effective digital audio watermarking using a deep convolutional neural network with a search location optimization algorithm for improvement in Robustness and Imperceptibility” [High-Confid. Comput. 3 (2023) 100153] 对 "利用深度卷积神经网络和搜索位置优化算法改进鲁棒性和不可感知性的有效数字音频水印 "的勘误 [High-Confid. Comput.

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-09-01 DOI: 10.1016/j.hcc.2024.100256

Abhijit J. Patil , Ramesh Shelke

引用次数: 0

A lightweight practical consensus mechanism for supply chain blockchain

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-06-28 DOI: 10.1016/j.hcc.2024.100253

Mohammad Saidur Rahman , Ibrahim Khalil , Mohammed Atiquzzaman , Abdelaziz Bouras

We present a consensus mechanism in this paper that is designed specifically for supply chain blockchains, with a core focus on establishing trust among participating stakeholders through a novel reputation-based approach. The prevailing consensus mechanisms, initially crafted for cryptocurrency applications, prove unsuitable for the unique dynamics of supply chain systems. Unlike the broad inclusivity of cryptocurrency networks, our proposed mechanism insists on stakeholder participation rooted in process-specific quality criteria. The delineation of roles for supply chain participants within the consensus process becomes paramount. While reputation serves as a well-established quality parameter in various domains, its nuanced impact on non-cryptocurrency consensus mechanisms remains uncharted territory. Moreover, recognizing the primary role of efficient block verification in blockchain-enabled supply chains, our work introduces a comprehensive reputation model. This model strategically selects a leader node to orchestrate the entire block mining process within the consensus. Additionally, we innovate with a Schnorr Multisignature-based block verification mechanism seamlessly integrated into our proposed consensus model. Rigorous experiments are conducted to evaluate the performance and feasibility of our pioneering consensus mechanism, contributing valuable insights to the evolving landscape of blockchain technology in supply chain applications.

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引用次数: 0

On Building Automation System security 楼宇自动化系统安全

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-05-27 DOI: 10.1016/j.hcc.2024.100236

Christopher Morales-Gonzalez , Matthew Harper , Michael Cash , Lan Luo , Zhen Ling , Qun Z. Sun , Xinwen Fu

Building Automation Systems (BASs) are seeing increased usage in modern society due to the plethora of benefits they provide such as automation for climate control, HVAC systems, entry systems, and lighting controls. Many BASs in use are outdated and suffer from numerous vulnerabilities that stem from the design of the underlying BAS protocol. In this paper, we provide a comprehensive, up-to-date survey on BASs and attacks against seven BAS protocols including BACnet, EnOcean, KNX, LonWorks, Modbus, ZigBee, and Z-Wave. Holistic studies of secure BAS protocols are also presented, covering BACnet Secure Connect, KNX Data Secure, KNX/IP Secure, ModBus/TCP Security, EnOcean High Security and Z-Wave Plus. LonWorks and ZigBee do not have security extensions. We point out how these security protocols improve the security of the BAS and what issues remain. A case study is provided which describes a real-world BAS and showcases its vulnerabilities as well as recommendations for improving the security of it. We seek to raise awareness to those in academia and industry as well as highlight open problems within BAS security.

由于楼宇自动化系统（BAS）具有气候控制自动化、暖通空调系统、入口系统和照明控制等诸多优点，因此在现代社会中的使用率越来越高。许多正在使用的楼宇自动化系统已经过时，并且存在许多源于底层楼宇自动化系统协议设计的漏洞。在本文中，我们对 BAS 以及针对七种 BAS 协议（包括 BACnet、EnOcean、KNX、LonWorks、Modbus、ZigBee 和 Z-Wave）的攻击进行了全面的最新调查。此外，还介绍了对安全 BAS 协议的全面研究，包括 BACnet Secure Connect、KNX Data Secure、KNX/IP Secure、ModBus/TCP Security、EnOcean High Security 和 Z-Wave Plus。LonWorks 和 ZigBee 没有安全扩展。我们指出了这些安全协议如何提高 BAS 的安全性，以及还存在哪些问题。我们还提供了一个案例研究，描述了现实世界中的一个 BAS，并展示了其漏洞以及改进其安全性的建议。我们力求提高学术界和工业界人士的认识，并强调 BAS 安全方面的未决问题。

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引用次数: 0

BAFL-SVM: A blockchain-assisted federated learning-driven SVM framework for smart agriculture BAFL-SVM：用于智慧农业的区块链辅助联合学习驱动 SVM 框架

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-05-23 DOI: 10.1016/j.hcc.2024.100243

Ruiyao Shen , Hongliang Zhang , Baobao Chai , Wenyue Wang , Guijuan Wang , Biwei Yan , Jiguo Yu

The combination of blockchain and Internet of Things technology has made significant progress in smart agriculture, which provides substantial support for data sharing and data privacy protection. Nevertheless, achieving efficient interactivity and privacy protection of agricultural data remains a crucial issues. To address the above problems, we propose a blockchain-assisted federated learning-driven support vector machine (BAFL-SVM) framework to realize efficient data sharing and privacy protection. The BAFL-SVM is composed of the FedSVM-RiceCare module and the FedPrivChain module. Specifically, in FedSVM-RiceCare, we utilize federated learning and SVM to train the model, improving the accuracy of the experiment. Then, in FedPrivChain, we adopt homomorphic encryption and a secret-sharing scheme to encrypt the local model parameters and upload them. Finally, we conduct a large number of experiments on a real-world dataset of rice pests and diseases, and the experimental results show that our framework not only guarantees the secure sharing of data but also achieves a higher recognition accuracy compared with other schemes.

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引用次数: 0

Balanced ID-OOD tradeoff transfer makes query based detectors good few shot learners 均衡的 ID-OOD 权衡转移使基于查询的检测器成为少数几个镜头的学习器

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-05-23 DOI: 10.1016/j.hcc.2024.100237

Yuantao Yin, Ping Yin, Xue Xiao, Liang Yan, Siqing Sun, Xiaobo An

Fine-tuning is a popular approach to solve the few-shot object detection problem. In this paper, we attempt to introduce a new perspective on it. We formulate the few-shot novel tasks as a type of distribution shifted from its ground-truth distribution. We introduce the concept of imaginary placeholder masks to show that this distribution shift is essentially a composite of in-distribution (ID) and out-of-distribution(OOD) shifts. Our empirical investigation results show that it is significant to balance the trade-off between adapting to the available few-shot distribution and keeping the distribution-shift robustness of the pre-trained model. We explore improvements in the few-shot fine-tuning transfer in the few-shot object detection (FSOD) settings from three aspects. First, we explore the LinearProbe-Finetuning (LP-FT) technique to balance this trade-off to mitigate the feature distortion problem. Second, we explore the effectiveness of utilizing the protection freezing strategy for query-based object detectors to keep their OOD robustness. Third, we try to utilize ensembling methods to circumvent the feature distortion. All these techniques are integrated into a whole method called BIOT (Balanced ID-OOD Transfer). Evaluation results show that our method is simple yet effective and general to tap the FSOD potential of query-based object detectors. It outperforms the current SOTA method in many FSOD settings and has a promising scaling capability.

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引用次数: 0

SoK: Decentralized Storage Network SoK：去中心化存储网络

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-05-22 DOI: 10.1016/j.hcc.2024.100239

Decentralized Storage Networks (DSNs) represent a paradigm shift in data storage methodology, distributing and housing data across multiple network nodes rather than relying on a centralized server or data center architecture. The fundamental objective of DSNs is to enhance security, reinforce reliability, and mitigate censorship risks by eliminating a single point of failure. Leveraging blockchain technology for functions such as access control, ownership validation, and transaction facilitation, DSN initiatives aim to provide users with a robust and secure alternative to traditional centralized storage solutions. This paper conducts a comprehensive analysis of the developmental trajectory of DSNs, focusing on key components such as Proof of Storage protocols, consensus algorithms, and incentive mechanisms. Additionally, the study explores recent optimization tactics, encountered challenges, and potential avenues for future research, thereby offering insights into the ongoing evolution and advancement within the DSN domain.

分散式存储网络（DSN）代表了数据存储方法的一种模式转变，它将数据分布和存储在多个网络节点上，而不是依赖于集中式服务器或数据中心架构。DSN 的基本目标是通过消除单点故障来提高安全性、加强可靠性和降低审查风险。利用区块链技术实现访问控制、所有权验证和交易促进等功能，DSN 计划旨在为用户提供一个强大而安全的替代方案，以取代传统的集中式存储解决方案。本文全面分析了 DSN 的发展轨迹，重点关注存储证明协议、共识算法和激励机制等关键组件。此外，本研究还探讨了最近的优化策略、遇到的挑战以及未来研究的潜在途径，从而为 DSN 领域的持续发展和进步提供了深入见解。

引用次数: 0

Exploring Personalized Internet of Things (PIoT), social connectivity, and Artificial Social Intelligence (ASI): A survey 探索个性化物联网（PIoT）、社交连接和人工智能（ASI）：调查

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-05-20 DOI: 10.1016/j.hcc.2024.100242

Pervasive Computing has become more personal with the widespread adoption of the Internet of Things (IoT) in our day-to-day lives. The emerging domain that encompasses devices, sensors, storage, and computing of personal use and surroundings leads to Personal IoT (PIoT). PIoT offers users high levels of personalization, automation, and convenience. This proliferation of PIoT technology has extended into society, social engagement, and the interconnectivity of PIoT objects, resulting in the emergence of the Social Internet of Things (SIoT). The combination of PIoT and SIoT has spurred the need for autonomous learning, comprehension, and understanding of both the physical and social worlds. Current research on PIoT is dedicated to enabling seamless communication among devices, striking a balance between observation, sensing, and perceiving the extended physical and social environment, and facilitating information exchange. Furthermore, the virtualization of independent learning from the social environment has given rise to Artificial Social Intelligence (ASI) in PIoT systems. However, autonomous data communication between different nodes within a social setup presents various resource management challenges that require careful consideration. This paper provides a comprehensive review of the evolving domains of PIoT, SIoT, and ASI. Moreover, the paper offers insightful modeling and a case study exploring the role of PIoT in post-COVID scenarios. This study contributes to a deeper understanding of the intricacies of PIoT and its various dimensions, paving the way for further advancements in this transformative field.

随着物联网（IoT）在日常生活中的广泛应用，普适计算变得更加个性化。个人物联网（PIoT）是一个新兴领域，包括个人使用和周围环境的设备、传感器、存储和计算。PIoT 为用户提供了高度的个性化、自动化和便利性。PIoT 技术的扩散已延伸到社会、社会参与和 PIoT 物体的互联性，从而导致了社会物联网（SIoT）的出现。PIoT 和 SIoT 的结合激发了人们对自主学习、理解和认识物理世界和社会世界的需求。目前有关 PIoT 的研究致力于实现设备之间的无缝通信，在观察、感知和感知扩展物理和社会环境之间取得平衡，并促进信息交流。此外，从社会环境中自主学习的虚拟化技术也催生了 PIoT 系统中的人工社会智能（ASI）。然而，社交环境中不同节点之间的自主数据通信带来了各种资源管理挑战，需要仔细考虑。本文对不断发展的 PIoT、SIoT 和 ASI 领域进行了全面回顾。此外，本文还提供了深入的建模和案例研究，探讨了 PIoT 在后 COVID 场景中的作用。本研究有助于加深对 PIoT 复杂性及其各个层面的理解，为这一变革性领域的进一步发展铺平道路。

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