High-Confidence Computing最新文献_第8页

Light field depth estimation: A comprehensive survey from principles to future 光场深度估计：从原理到未来的全面考察

High-Confidence Computing Pub Date : 2023-11-22 DOI: 10.1016/j.hcc.2023.100187

Tun Wang , Hao Sheng , Rongshan Chen , Da Yang , Zhenglong Cui , Sizhe Wang , Ruixuan Cong , Mingyuan Zhao

{"title":"Light field depth estimation: A comprehensive survey from principles to future","authors":"Tun Wang , Hao Sheng , Rongshan Chen , Da Yang , Zhenglong Cui , Sizhe Wang , Ruixuan Cong , Mingyuan Zhao","doi":"10.1016/j.hcc.2023.100187","DOIUrl":"10.1016/j.hcc.2023.100187","url":null,"abstract":"<div><p>Light Field (LF) depth estimation is an important research direction in the area of computer vision and computational photography, which aims to infer the depth information of different objects in three-dimensional scenes by capturing LF data. Given this new era of significance, this article introduces a survey of the key concepts, methods, novel applications, and future trends in this area. We summarize the LF depth estimation methods, which are usually based on the interaction of radiance from rays in all directions of the LF data, such as epipolar-plane, multi-view geometry, focal stack, and deep learning. We analyze the many challenges facing each of these approaches, including complex algorithms, large amounts of computation, and speed requirements. In addition, this survey summarizes most of the currently available methods, conducts some comparative experiments, discusses the results, and investigates the novel directions in LF depth estimation.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 1","pages":"Article 100187"},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000855/pdfft?md5=995254b6e9fd71f7ac04f1e9668cefdf&pid=1-s2.0-S2667295223000855-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139294487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A self-driving solution for resource-constrained autonomous vehicles in parked areas 停放区资源受限自动驾驶车辆的自动驾驶解决方案

High-Confidence Computing Pub Date : 2023-11-22 DOI: 10.1016/j.hcc.2023.100182

Jin Qian , Liang Zhang , Qiwei Huang , Xinyi Liu , Xiaoshuang Xing , Xuehan Li

{"title":"A self-driving solution for resource-constrained autonomous vehicles in parked areas","authors":"Jin Qian , Liang Zhang , Qiwei Huang , Xinyi Liu , Xiaoshuang Xing , Xuehan Li","doi":"10.1016/j.hcc.2023.100182","DOIUrl":"10.1016/j.hcc.2023.100182","url":null,"abstract":"<div><p>Autonomous vehicles in industrial parks can provide intelligent, efficient, and environmentally friendly transportation services, making them crucial tools for solving internal transportation issues. Considering the characteristics of industrial park scenarios and limited resources, designing and implementing autonomous driving solutions for autonomous vehicles in these areas has become a research hotspot. This paper proposes an efficient autonomous driving solution based on path planning, target recognition, and driving decision-making as its core components. Detailed designs for path planning, lane positioning, driving decision-making, and anti-collision algorithms are presented. Performance analysis and experimental validation of the proposed solution demonstrate its effectiveness in meeting the autonomous driving needs within resource-constrained environments in industrial parks. This solution provides important references for enhancing the performance of autonomous vehicles in these areas.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 1","pages":"Article 100182"},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000806/pdfft?md5=6cc55cff8f575313ade27c7955e65ccd&pid=1-s2.0-S2667295223000806-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139292239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural-based inexact graph de-anonymization 基于神经的非精确图形去匿名化

High-Confidence Computing Pub Date : 2023-11-22 DOI: 10.1016/j.hcc.2023.100186

Guangxi Lu , Kaiyang Li , Xiaotong Wang , Ziyue Liu , Zhipeng Cai , Wei Li

{"title":"Neural-based inexact graph de-anonymization","authors":"Guangxi Lu , Kaiyang Li , Xiaotong Wang , Ziyue Liu , Zhipeng Cai , Wei Li","doi":"10.1016/j.hcc.2023.100186","DOIUrl":"https://doi.org/10.1016/j.hcc.2023.100186","url":null,"abstract":"<div><p>Graph de-anonymization is a technique used to reveal connections between entities in anonymized graphs, which is crucial in detecting malicious activities, network analysis, social network analysis, and more. Despite its paramount importance, conventional methods often grapple with inefficiencies and challenges tied to obtaining accurate query graph data. This paper introduces a neural-based inexact graph de-anonymization, which comprises an embedding phase, a comparison phase, and a matching procedure. The embedding phase uses a graph convolutional network to generate embedding vectors for both the query and anonymized graphs. The comparison phase uses a neural tensor network to ascertain node resemblances. The matching procedure employs a refined greedy algorithm to discern optimal node pairings. Additionally, we comprehensively evaluate its performance via well-conducted experiments on various real datasets. The results demonstrate the effectiveness of our proposed approach in enhancing the efficiency and performance of graph de-anonymization through the use of graph embedding vectors.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 1","pages":"Article 100186"},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000843/pdfft?md5=0d8fc958c3885f06c72a47da20a82a5f&pid=1-s2.0-S2667295223000843-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139033378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An insider user authentication method based on improved temporal convolutional network 一种基于改进时间卷积网络的内部用户认证方法

High-Confidence Computing Pub Date : 2023-11-13 DOI: 10.1016/j.hcc.2023.100169

Xiaoling Tao, Yuelin Yu, Lianyou Fu, Jianxiang Liu, Yunhao Zhang

{"title":"An insider user authentication method based on improved temporal convolutional network","authors":"Xiaoling Tao, Yuelin Yu, Lianyou Fu, Jianxiang Liu, Yunhao Zhang","doi":"10.1016/j.hcc.2023.100169","DOIUrl":"10.1016/j.hcc.2023.100169","url":null,"abstract":"<div><p>With the rapid development of information technology, information system security and insider threat detection have become important topics for organizational management. In the current network environment, user behavioral bio-data presents the characteristics of nonlinearity and temporal sequence. Most of the existing research on authentication based on user behavioral biometrics adopts the method of manual feature extraction. They do not adequately capture the nonlinear and time-sequential dependencies of behavioral bio-data, and also do not adequately reflect the personalized usage characteristics of users, leading to bottlenecks in the performance of the authentication algorithm. In order to solve the above problems, this paper proposes a Temporal Convolutional Network method based on an Efficient Channel Attention mechanism (ECA-TCN) to extract user mouse dynamics features and constructs an one-class Support Vector Machine (OCSVM) for each user for authentication. Experimental results show that compared with four existing deep learning algorithms, the method retains more adequate key information and improves the classification performance of the neural network. In the final authentication, the Area Under the Curve (AUC) can reach 96%.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"3 4","pages":"Article 100169"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000673/pdfft?md5=e3a2018fd567973462b834311553fa94&pid=1-s2.0-S2667295223000673-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135714997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance of unique and secure routing protocol (USRP) in flying Adhoc Networks for healthcare applications 用于医疗保健应用的飞行 Adhoc 网络中独特安全路由协议 (USRP) 的性能

High-Confidence Computing Pub Date : 2023-11-11 DOI: 10.1016/j.hcc.2023.100170

J. Vijitha Ananthi, P. Subha Hency Jose

{"title":"Performance of unique and secure routing protocol (USRP) in flying Adhoc Networks for healthcare applications","authors":"J. Vijitha Ananthi, P. Subha Hency Jose","doi":"10.1016/j.hcc.2023.100170","DOIUrl":"10.1016/j.hcc.2023.100170","url":null,"abstract":"<div><p>Nowadays, Flying Adhoc Networks play a vital role due to its high efficiency in fast communication. Unmanned aerial vehicles transmit data much faster than other networks and are useful in all aspects of communication. In healthcare applications, wireless body area network transmits the data, whereas the security, which is the most important concern to be focused in a flying adhoc network is not satisfactory. Many intruders tamper the network, degrading the overall network performance. To avoid security issues, a unique and secure routing protocol that provides a single solution for five different types of attacks such as, black hole attacks, grey hole attacks, yoyo attacks, conjoint attack and jamming attacks, is proposed. The simulation results analyses the network performance by using the proposed routing table. In comparison to the other solutions rendered to resolve the affected network, this proposed routing protocol has a higher throughput, higher delivery rate, and lower delay. The Unique and Secure Routing Protocol (USRP) provides an integrated solution for an efficient and secure communication in a flying adhoc network.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 1","pages":"Article 100170"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000685/pdfft?md5=71d26afc95d290cd3a4efa882f8e618a&pid=1-s2.0-S2667295223000685-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135663879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Redactable consortium blockchain with access control: Leveraging chameleon hash and multi-authority attribute-based encryption 具有访问控制功能的可重删联盟区块链：利用变色龙哈希和基于属性的多授权加密技术

High-Confidence Computing Pub Date : 2023-11-07 DOI: 10.1016/j.hcc.2023.100168

Yueyan Dong, Yifang Li, Ye Cheng, Dongxiao Yu

{"title":"Redactable consortium blockchain with access control: Leveraging chameleon hash and multi-authority attribute-based encryption","authors":"Yueyan Dong, Yifang Li, Ye Cheng, Dongxiao Yu","doi":"10.1016/j.hcc.2023.100168","DOIUrl":"10.1016/j.hcc.2023.100168","url":null,"abstract":"<div><p>A redactable blockchain allows authorized individuals to remove or replace undesirable content, offering the ability to remove illegal or unwanted information. Access control is a mechanism that limits data visibility and ensures that only authorized users can decrypt and access encrypted information, playing a crucial role in addressing privacy concerns and securing the data stored on a blockchain. Redactability and access control are both essential components when implementing a regulated consortium blockchain in real-world situations to ensure the secure sharing of data while removing undesirable content. We propose a decentralized consortium blockchain system prototype that supports redactability and access control. Through the development of a prototype blockchain system, we investigate the feasibility of combining these approaches and demonstrate that it is possible to implement a redactable blockchain with access control in a consortium blockchain setting.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 1","pages":"Article 100168"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000661/pdfft?md5=354cdeda692d0ad1d062d3b27e03c072&pid=1-s2.0-S2667295223000661-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135510456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Security defense strategy algorithm for Internet of Things based on deep reinforcement learning 基于深度强化学习的物联网安全防御策略算法

High-Confidence Computing Pub Date : 2023-10-12 DOI: 10.1016/j.hcc.2023.100167

Xuecai Feng, Jikai Han, Rui Zhang, Shuo Xu, Hui Xia

{"title":"Security defense strategy algorithm for Internet of Things based on deep reinforcement learning","authors":"Xuecai Feng, Jikai Han, Rui Zhang, Shuo Xu, Hui Xia","doi":"10.1016/j.hcc.2023.100167","DOIUrl":"10.1016/j.hcc.2023.100167","url":null,"abstract":"<div><p>Currently, important privacy data of the Internet of Things (IoT) face extremely high risks of leakage. Attackers persistently engage in continuous attacks on terminal devices to obtain private data of crucial importance. Although significant progress has been made in recent years in deep reinforcement learning defense strategies, most defense methods still face problems such as low defense resource allocation efficiency and insufficient defense coordination capabilities. To solve the above problems, this paper constructs a novel adversarial security scenario and proposes a security game model that integrates defense resource allocation and patrol inspection. Regarding the above game model, this paper designs a deep reinforcement learning algorithm named SDSA to calculate its security defense strategy. SDSA calculates the allocation strategy of the best patrolling strategy that is most suitable for the defender by searching the policy on a multi-dimensional discrete action space, and enables multiple defense agents to cooperate efficiently by training a multi-intelligent Dueling Double Deep Q-Network (D3QN) with prioritized experience replay. Finally, the experimental results show that the SDSA-learned security defense strategy can provide a feasible and effective security protection strategy for defenders against attacks compared to the MADDPG and OptGradFP methods.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 1","pages":"Article 100167"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266729522300065X/pdfft?md5=5ba5e4cf27f862d15547b114a55810e3&pid=1-s2.0-S266729522300065X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135707986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning job failure analysis and prediction model for the cloud environment 面向云环境的机器学习作业失效分析与预测模型

High-Confidence Computing Pub Date : 2023-09-27 DOI: 10.1016/j.hcc.2023.100165

Harikrishna Bommala , Uma Maheswari V. , Rajanikanth Aluvalu , Swapna Mudrakola

{"title":"Machine learning job failure analysis and prediction model for the cloud environment","authors":"Harikrishna Bommala , Uma Maheswari V. , Rajanikanth Aluvalu , Swapna Mudrakola","doi":"10.1016/j.hcc.2023.100165","DOIUrl":"10.1016/j.hcc.2023.100165","url":null,"abstract":"<div><p>Reliable and accessible cloud applications are essential for the future of ubiquitous computing, smart appliances, and electronic health. Owing to the vastness and diversity of the cloud, a most cloud services, both physical and logical services have failed. Using currently accessible traces, we assessed and characterized the behaviors of successful and unsuccessful activities. We devised and implemented a method to forecast which jobs will fail. The proposed method optimizes cloud applications more efficiently in terms of resource usage. Using Google Cluster, Mustang, and Trinity traces, which are publicly available, an in-depth evaluation of the proposed model was conducted. The traces were also fed into several different machine learning models to select the most reliable model. Our efficiency analysis proves that the model performs well in terms of accuracy, F1-score, and recall. Several factors, such as failure of forecasting work, design of scheduling algorithms, modification of priority criteria, and restriction of task resubmission, may increase cloud service dependability and availability.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"3 4","pages":"Article 100165"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000636/pdfft?md5=bfe61b5b8fb7fd53b685e1c9be60171b&pid=1-s2.0-S2667295223000636-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134995410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decoupled knowledge distillation method based on meta-learning 基于元学习的解耦知识蒸馏方法

High-Confidence Computing Pub Date : 2023-09-26 DOI: 10.1016/j.hcc.2023.100164

Wenqing Du , Liting Geng , Jianxiong Liu , Zhigang Zhao , Chunxiao Wang , Jidong Huo

引用次数: 0

A study on dynamic group signature scheme with threshold traceability for blockchain 带阈值可追溯性的区块链动态群组签名方案研究

High-Confidence Computing Pub Date : 2023-09-20 DOI: 10.1016/j.hcc.2023.100163

Hyo-jin Song , Teahoon Kim , Yong-Woon Hwang , Daehee Seo , Im-Yeong Lee

{"title":"A study on dynamic group signature scheme with threshold traceability for blockchain","authors":"Hyo-jin Song , Teahoon Kim , Yong-Woon Hwang , Daehee Seo , Im-Yeong Lee","doi":"10.1016/j.hcc.2023.100163","DOIUrl":"10.1016/j.hcc.2023.100163","url":null,"abstract":"<div><p>Blockchain technology provides transparency and reliability by sharing transactions and maintaining the same information through consensus among all participants. However, single-signature applications in transactions can lead to user identification issues due to the reuse of public keys. To address this issue, group signatures can be used, where the same group public key is used to verify signatures from group members to provide anonymity to users. However, in dynamic groups where membership may change, an attack can occur where a user who has left the group can disguise themselves as a group member by leaking a partial key. This problem cannot be traced back to the partial key leaker. In this paper, we propose assigning different partial keys to group members to trace partial key leakers and partially alleviate the damage caused by partial key leaks. Exist schemes have shown that arbitrary tracing issues occurred when a single administrator had exclusive key generation and tracing authority. This paper proposes a group signature scheme that solves the synchronization problem by involving a threshold number of TMs while preventing arbitrary tracing by distributing authority among multiple TMs.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100163"},"PeriodicalIF":0.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000612/pdfft?md5=f44628d3083bf96e8f4a13831b67a184&pid=1-s2.0-S2667295223000612-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135387621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0