High-Confidence Computing最新文献_第8页

A study on an efficient OSS inspection scheme based on encrypted GML 基于加密GML的OSS检测方案研究

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-11-05 DOI: 10.1016/j.hcc.2024.100279

Seok-Joon Jang , Im-Yeong Lee , Daehee Seo , Su-Hyun Kim

The importance of Open Source Software (OSS) has increased in recent years. OSS is software that is jointly developed and maintained globally through open collaboration and knowledge sharing. OSS plays an important role, especially in the Information Technology (IT) field, by increasing the efficiency of software development and reducing costs. However, licensing issues, security issues, etc., may arise when using OSS. Some services analyze source code and provide OSS-related data to solve these problems, a representative example being Blackduck. Blackduck inspects the entiresource code within the project and provides OSS information and related data included in the whole project. Therefore, there are problems such as inefficiency due to full inspection of the source code and difficulty in determining the exact location where OSS is identified. This paper proposes a scheme to intuitively analyze source code through Graph Modelling Language (GML) conversion to solve these problems. Additionally, encryption is applied to GML to performsecure GML-based OSS inspection. The study explains the process of converting source code to GML and performing OSS inspection. Afterward, we compare the capacity and accuracy of text-based OSS inspection and GML-based OSS inspection. Signcryption is applied to performsafe, GML-based, efficient OSS inspection.

近年来，开源软件（OSS）的重要性与日俱增。OSS是通过开放协作和知识共享在全球范围内共同开发和维护的软件。OSS通过提高软件开发效率和降低成本，在信息技术（IT）领域发挥着重要作用。但是，在使用OSS时可能会出现许可问题、安全问题等。一些服务分析源代码并提供oss相关数据来解决这些问题，代表性的例子是Blackduck。Blackduck检查项目内的整个资源代码，并提供整个项目中包含的OSS信息和相关数据。因此，存在一些问题，例如由于源代码的全面检查而导致的效率低下，以及难以确定识别OSS的确切位置。本文提出了一种通过图形建模语言（GML）转换对源代码进行直观分析的方案来解决这些问题。另外，对GML进行加密，实现基于GML的安全OSS检查。该研究解释了将源代码转换为GML和执行OSS检查的过程。然后，我们比较了基于文本的OSS检测和基于gml的OSS检测的容量和准确性。签名加密用于执行安全、基于gml、高效的OSS检查。

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引用次数: 0

Joint feature selection and classification of low-resolution satellite images using the SAT-6 dataset 基于SAT-6数据集的低分辨率卫星图像联合特征选择与分类

IF 3 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-11-05 DOI: 10.1016/j.hcc.2024.100278

Rajalaxmi Padhy, Sanjit Kumar Dash, Jibitesh Mishra

The modern industries of today demand the classification of satellite images, and to use the information obtained from it for their advantage and growth. The extracted information also plays a crucial role in national security and the mapping of geographical locations. The conventional methods often fail to handle the complexities of this process. So, an effective method is required with high accuracy and stability. In this paper, a new methodology named RankEnsembleFS is proposed that addresses the crucial issues of stability and feature aggregation in the context of the SAT-6 dataset. RankEnsembleFS makes use of a two-step process that consists of ranking the features and then selecting the optimal feature subset from the top-ranked features. RankEnsembleFS achieved comparable accuracy results to state-of-the-art models for the SAT-6 dataset while significantly reducing the feature space. This reduction in feature space is important because it reduces computational complexity and enhances the interpretability of the model. Moreover, the proposed method demonstrated good stability in handling changes in data characteristics, which is critical for reliable performance over time and surpasses existing ML ensemble methods in terms of stability, threshold setting, and feature aggregation. In summary, this paper provides compelling evidence that this RankEnsembleFS methodology presents excellent performance and overcomes key issues in feature selection and image classification for the SAT-6 dataset.

今天的现代工业需要对卫星图像进行分类，并利用从中获得的信息来获得优势和发展。提取的信息在国家安全和地理位置测绘中也起着至关重要的作用。传统方法往往无法处理这一过程的复杂性。因此，需要一种精度高、稳定性好的有效方法。本文提出了一种名为RankEnsembleFS的新方法，该方法解决了SAT-6数据集背景下稳定性和特征聚合的关键问题。RankEnsembleFS使用了一个两步过程，包括对特征进行排序，然后从排名靠前的特征中选择最优的特征子集。RankEnsembleFS取得了与SAT-6数据集的最先进模型相当的精度结果，同时显着减少了特征空间。特征空间的减少很重要，因为它降低了计算复杂度并增强了模型的可解释性。此外，该方法在处理数据特征变化方面表现出良好的稳定性，这对于长期可靠的性能至关重要，并且在稳定性、阈值设置和特征聚合方面优于现有的ML集成方法。总之，本文提供了令人信服的证据，表明这种RankEnsembleFS方法具有出色的性能，并克服了SAT-6数据集的特征选择和图像分类中的关键问题。

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引用次数: 0

IDL-LTSOJ: Research and implementation of an intelligent online judge system utilizing DNN for defect localization IDL-LTSOJ：基于深度神经网络的缺陷定位智能在线判断系统的研究与实现

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-11-01 DOI: 10.1016/j.hcc.2024.100268

Lihua Song , Ying Han , Yufei Guo , Chenying Cai

The evolution of artificial intelligence has thrust the Online Judge (OJ) systems into the forefront of research, particularly within programming education, with a focus on enhancing performance and efficiency. Addressing the shortcomings of the current OJ systems in coarse defect localization granularity and heavy task scheduling architecture, this paper introduces an innovative Integrated Intelligent Defect Localization and Lightweight Task Scheduling Online Judge (IDL-LTSOJ) system. Firstly, to achieve token-level fine-grained defect localization, a Deep Fine-Grained Defect Localization (Deep-FGDL) deep neural network model is developed. By integrating Bidirectional Long Short-Term Memory (BiLSTM) and Bidirectional Gated Recurrent Unit (BiGRU), this model extracts fine-grained information from the abstract syntax tree (AST) of code, enabling more accurate defect localization. Subsequently, we propose a lightweight task scheduling architecture to tackle issues, such as limited concurrency in task evaluation and high equipment costs. This architecture integrates a Kafka messaging system with an optimized task distribution strategy to enable concurrent execution of evaluation tasks, substantially enhancing system evaluation efficiency. The experimental results demonstrate that the Deep-FGDL model improves the accuracy by 35.9% in the Top-20 rank compared to traditional machine learning benchmark methods for fine-grained defect localization tasks. Moreover, the lightweight task scheduling strategy notably reduces response time by nearly 6000ms when handling 120 task volumes, which represents a significant improvement in evaluation efficiency over centralized evaluation methods.

人工智能的发展将在线裁判（OJ）系统推向了研究的前沿，特别是在编程教育领域，其重点是提高性能和效率。针对现有OJ系统存在缺陷定位粒度粗、任务调度架构繁重的缺点，提出了一种创新的集成智能缺陷定位与轻量级任务调度在线判断系统（IDL-LTSOJ）。首先，为了实现标记级细粒度缺陷定位，建立了深度细粒度缺陷定位（Deep- fgdl）深度神经网络模型；该模型通过集成双向长短期记忆（BiLSTM）和双向门控循环单元（BiGRU），从代码的抽象语法树（AST）中提取细粒度信息，实现更准确的缺陷定位。随后，我们提出了一种轻量级的任务调度架构，以解决任务评估并发性有限和设备成本高的问题。该架构将Kafka消息传递系统与优化的任务分发策略集成在一起，实现了评估任务的并发执行，大大提高了系统评估效率。实验结果表明，对于细粒度缺陷定位任务，与传统机器学习基准方法相比，Deep-FGDL模型的准确率在Top-20排名中提高了35.9%。此外，当处理120个任务量时，轻量级任务调度策略显著减少了近6000ms的响应时间，与集中式评估方法相比，这代表了评估效率的显著提高。

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引用次数: 0

A novel deep high-level concept-mining jointing hashing model for unsupervised cross-modal retrieval 一种新的用于无监督跨模态检索的深度高级概念挖掘连接哈希模型

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-10-29 DOI: 10.1016/j.hcc.2024.100274

Chun-Ru Dong , Jun-Yan Zhang , Feng Zhang , Qiang Hua , Dachuan Xu

Unsupervised cross-modal hashing has achieved great success in various information retrieval applications owing to its efficient storage usage and fast retrieval speed. Recent studies have primarily focused on training the hash-encoded networks by calculating a sample-based similarity matrix to improve the retrieval performance. However, there are two issues remain to solve: (1) The current sample-based similarity matrix only considers the similarity between image-text pairs, ignoring the different information densities of each modality, which may introduce additional noise and fail to mine key information for retrieval; (2) Most existing unsupervised cross-modal hashing methods only consider alignment between different modalities, while ignoring consistency between each modality, resulting in semantic conflicts. To tackle these challenges, a novel Deep High-level Concept-mining Jointing Hashing (DHCJH) model for unsupervised cross-modal retrieval is proposed in this study. DHCJH is able to capture the essential high-level semantic information from image modalities and integrate into the text modalities to improve the accuracy of guidance information. Additionally, a new hashing loss with a regularization term is introduced to avoid the cross-modal semantic collision and false positive pairs problems. To validate the proposed method, extensive comparison experiments on benchmark datasets are conducted. Experimental findings reveal that DHCJH achieves superior performance in both accuracy and efficiency. The code of DHCJH is available at Github.

无监督跨模态哈希以其高效的存储利用率和快速的检索速度在各种信息检索应用中取得了巨大的成功。最近的研究主要集中在通过计算基于样本的相似性矩阵来训练哈希编码网络，以提高检索性能。然而，目前基于样本的相似度矩阵只考虑图像-文本对之间的相似度，忽略了每种模态的不同信息密度，这可能会引入额外的噪声，无法挖掘关键信息进行检索；(2)现有的大多数无监督跨模态哈希方法只考虑了不同模态之间的对齐，而忽略了各模态之间的一致性，导致语义冲突。为了解决这些问题，本研究提出了一种新的用于无监督跨模态检索的深度高级概念挖掘连接哈希（DHCJH）模型。DHCJH能够从图像模态中捕获重要的高级语义信息，并将其整合到文本模态中，以提高制导信息的准确性。此外，引入了一种新的带正则化项的哈希损失，避免了跨模态语义冲突和假正对问题。为了验证所提出的方法，在基准数据集上进行了大量的对比实验。实验结果表明，DHCJH在准确率和效率方面都取得了优异的成绩。DHCJH的代码可在Github上获得。

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引用次数: 0

MCLORA: Maritime ad-hoc communication system based on LORA MCLORA：基于LORA的海上自组织通信系统

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-10-28 DOI: 10.1016/j.hcc.2024.100275

Jie Zhang, Hui Liu, Yusheng He, Wei Gao, Nannan Xu, Chao Liu

Maritime communication plays a crucial role in fields such as ocean resource exploration and marine environmental monitoring. Existing maritime communication methods either face challenges in equipment deployment or are limited by high power requirements, making sustained operation difficult. The emergence of LoRa presents an opportunity in this regard, with its characteristics of low power consumption and long communication range, meeting the demands for long-term maritime communication. However, LoRa’s underlying implementation is not open-source, and LoRaWAN itself adopts a star topology, limiting communication between nodes. Therefore, we have devised a communication packet header working at the application layer to enable peer-to-peer communication between nodes. Our on-campus field tests have shown that our system can achieve node-to-node communication, networking functionalities, with a packet delivery rate more than 94%, and max data transmission rate can achieve 1027 bps. In the sea test, the communication rate of our node remained basically around 1035 bps due to the absence of objects blocking the line of sight, and packet delivery rate was more than 96%. The byte error rates of all experiments were less than 0.5%.

海洋通信在海洋资源勘探、海洋环境监测等领域发挥着至关重要的作用。现有的海上通信方法要么面临设备部署方面的挑战，要么受到高功率要求的限制，难以持续运行。LoRa的出现为这方面提供了机会，其功耗低，通信距离远的特点，满足了长期海上通信的需求。但是，LoRa的底层实现不是开源的，而且LoRaWAN本身采用星型拓扑，限制了节点之间的通信。因此，我们设计了一个在应用层工作的通信包头，以实现节点之间的点对点通信。我们的校园现场测试表明，我们的系统可以实现节点到节点的通信、联网功能，数据包传输率超过94%，最大数据传输率可以达到1027bps。在海上测试中，由于没有遮挡视线的物体，我们节点的通信速率基本保持在1035bps左右，数据包的投递率在96%以上。所有实验的字节错误率均小于0.5%。

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引用次数: 0

Minimizing charging task time of WRSN assisted with multiple MUVs and laser-charged UAVs 最小化WRSN在多muv和激光充电无人机辅助下的充电任务时间

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-10-05 DOI: 10.1016/j.hcc.2024.100272

Jian Zhang , Chuanwen Luo , Ning Liu , Yi Hong , Zhibo Chen

This paper investigates the framework of wireless rechargeable sensor network (WRSN) assisted by multiple mobile unmanned vehicles (MUVs) and laser-charged unmanned aerial vehicles (UAVs). On the basis of framework, we cooperatively investigate the trajectory optimization of multi-UAVs and multi-MUVs for charging WRSN (TOUM) problem, whose goal aims at designing the optimal travel plan of UAVs and MUVs cooperatively to charge WRSN such that the remaining energy of each sensor in WRSN is greater than or equal to the threshold and the time consumption of UAV that takes the most time of all UAVs is minimized. The TOUM problem is proved NP-hard. To solve the TOUM problem, we first investigate the multiple UAVs-based TSP (MUTSP) problem to balance the charging tasks assigned to every UAV. Then, based on the MUTSP problem, we propose the TOUM algorithm (TOUMA) to design the detailed travel plan of UAVs and MUVs. We also present an algorithm named TOUM-DQN to make intelligent decisions about the travel plan of UAVs and MUVs by extracting valuable information from the network. The effectiveness of proposed algorithms is verified through extensive simulation experiments. The results demonstrate that the TOUMA algorithm outperforms the solar charging method, the base station charging method, and the TOUM-DQN algorithm in terms of time efficiency. Simultaneously, the experimental results show that the execution time of TOUM-DQN algorithm is significantly lower than TOUMA algorithm.

研究了由多辆移动无人车（muv）和激光充电无人机（uav）辅助的无线可充电传感器网络（WRSN）的框架。在此框架的基础上，我们合作研究了多无人机多muv为WRSN充电的轨迹优化（图）问题，其目标是设计出无人机和muv协同充电WRSN的最优行程方案，使WRSN中每个传感器的剩余能量大于等于阈值，同时使耗时最多的无人机的时间消耗最小。图姆问题被证明是np困难的。为了解决图姆问题，我们首先研究了基于多无人机的TSP （MUTSP）问题，以平衡分配给每架无人机的收费任务。然后，在MUTSP问题的基础上，提出了图马算法（TOUMA）来设计无人机和多用途机动车辆的详细出行计划。本文还提出了一种名为TOUM-DQN的算法，通过从网络中提取有价值的信息，对无人机和机动车辆的旅行计划进行智能决策。通过大量的仿真实验验证了所提算法的有效性。结果表明，在时间效率方面，TOUMA算法优于太阳能充电法、基站充电法和TOUM-DQN算法。同时，实验结果表明，TOUMA - dqn算法的执行时间明显低于TOUMA算法。

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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

Trusted access control mechanism for data with blockchain-assisted attribute encryption 区块链辅助属性加密数据可信访问控制机制

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

High-Confidence Computing

Pub Date : 2024-08-31 DOI: 10.1016/j.hcc.2024.100265

Chang Liu , Dong Wang , Da Li , Shaoyong Guo , Wenjing Li , Xuesong Qiu

In the growing demand for data sharing, how to realize fine-grained trusted access control of shared data and protect data security has become a difficult problem. Ciphertext policy attribute-based encryption (CP-ABE) model is widely used in cloud data sharing scenarios, but there are problems such as privacy leakage of access policy, irrevocability of user or attribute, key escrow, and trust bottleneck. Therefore, we propose a blockchain-assisted CP-ABE (B-CP-ABE) mechanism for trusted data access control. Firstly, we construct a data trusted access control architecture based on the B-CP-ABE, which realizes the automated execution of access policies through smart contracts and guarantees the trusted access process through blockchain. Then, we define the B-CP-ABE scheme, which has the functions of policy partial hidden, attribute revocation, and anti-key escrow. The B-CP-ABE scheme utilizes Bloom filter to hide the mapping relationship of sensitive attributes in the access structure, realizes flexible revocation and recovery of users and attributes by re-encryption algorithm, and solves the key escrow problem by joint authorization of data owners and attribute authority. Finally, we demonstrate the usability of the B-CP-ABE scheme by performing security analysis and performance analysis.

在日益增长的数据共享需求中，如何实现对共享数据的细粒度可信访问控制，保护数据安全成为一个难题。基于密文策略属性的加密（cipher policy attribute-based encryption, CP-ABE）模型广泛应用于云数据共享场景，但存在访问策略隐私泄露、用户或属性不可撤销、密钥托管、信任瓶颈等问题。因此，我们提出了一种区块链辅助的CP-ABE （B-CP-ABE）机制，用于可信数据访问控制。首先，我们构建了基于B-CP-ABE的数据可信访问控制体系结构，通过智能合约实现访问策略的自动执行，并通过区块链保证可信访问过程。然后，我们定义了具有策略部分隐藏、属性撤销和反密钥托管功能的B-CP-ABE方案。B-CP-ABE方案利用Bloom过滤器隐藏访问结构中敏感属性的映射关系，通过重加密算法实现用户和属性的灵活撤销和恢复，并通过数据所有者和属性权限的联合授权解决密钥托管问题。最后，通过安全性分析和性能分析验证了B-CP-ABE方案的可用性。

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引用次数: 0