High-Confidence Computing最新文献

Blockchain-based inter-operator settlement system 基于区块链的运营商间结算系统

IF 3.2

High-Confidence Computing Pub Date : 2025-04-30 DOI: 10.1016/j.hcc.2025.100324

Shifu Zhang, Yulin Pan

{"title":"Blockchain-based inter-operator settlement system","authors":"Shifu Zhang, Yulin Pan","doi":"10.1016/j.hcc.2025.100324","DOIUrl":"10.1016/j.hcc.2025.100324","url":null,"abstract":"<div><div>Inter-network settlement is a critical mechanism for ensuring quality service and sustainable growth in the telecommunications industry. However, existing practices among operators suffer from inefficient, including manual workflows, untrustworthy data foundations, insecure dispute resolution, and insufficient accountability oversight. These challenges lead to prolonged settlement cycles, operational redundancies, and heightened risks of errors or leaks. To address these issues, we propose a blockchain-powered settlement chain framework that integrates business and technical systems to enable intelligent, trusted, and automated cross-operator settlement management. By synergizing consortium blockchain, privacy-preserving computation, and decentralized governance protocols, the framework establishes an end-to-end digital workflow covering data exchange, verification, auditing, and reconciliation. Key innovations include: (1) a multi-operator co-built consortium chain with cross-cloud networking and peer-to-peer governance; (2) a “data-available-but-invisible” auditing mechanism combining blockchain and privacy-preserving computation to ensure secure, compliant interactions; and (3) a dynamic chaincode architecture supporting real-time rule synchronization and adaptive cryptographic controls. The framework achieves full-process traceability, automated reconciliation, and enhanced financial governance while reducing reliance on manual intervention. This work provides a transformative paradigm for modernizing telecommunications settlement systems through digital trust infrastructure.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 2","pages":"Article 100324"},"PeriodicalIF":3.2,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Task migration with deadlines using machine learning-based dwell time prediction in vehicular micro clouds 基于机器学习的车辆微云停留时间预测的任务迁移

IF 3.2

High-Confidence Computing Pub Date : 2025-03-03 DOI: 10.1016/j.hcc.2025.100314

Ziqi Zhou , Agon Memedi , Chunghan Lee , Seyhan Ucar , Onur Altintas , Falko Dressler

{"title":"Task migration with deadlines using machine learning-based dwell time prediction in vehicular micro clouds","authors":"Ziqi Zhou , Agon Memedi , Chunghan Lee , Seyhan Ucar , Onur Altintas , Falko Dressler","doi":"10.1016/j.hcc.2025.100314","DOIUrl":"10.1016/j.hcc.2025.100314","url":null,"abstract":"<div><div>Edge computing is becoming ever more relevant to offload compute-heavy tasks in vehicular networks. In this context, the concept of vehicular micro clouds (VMCs) has been proposed to use compute and storage resources on nearby vehicles to complete computational tasks. As many tasks in this application domain are time critical, offloading to the cloud is prohibitive. Additionally, task deadlines have to be dealt with. This paper addresses two main challenges. First, we present a task migration algorithm supporting deadlines in vehicular edge computing. The algorithm is following the earliest deadline first model but in presence of dynamic processing resources, <em>i.e</em>, vehicles joining and leaving a VMC. This task offloading is very sensitive to the mobility of vehicles in a VMC, <em>i.e</em>, the so-called dwell time a vehicles spends in the VMC. Thus, secondly, we propose a machine learning-based solution for dwell time prediction. Our dwell time prediction model uses a random forest approach to estimate how long a vehicle will stay in a VMC. Our approach is evaluated using mobility traces of an artificial simple intersection scenario as well as of real urban traffic in cities of Luxembourg and Nagoya. Our proposed approach is able to realize low-delay and low-failure task migration in dynamic vehicular conditions, advancing the state of the art in vehicular edge computing.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 2","pages":"Article 100314"},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On protecting the data privacy of Large Language Models (LLMs) and LLM agents: A literature review 大型语言模型（LLM）及其代理的数据隐私保护：文献综述

IF 3.2

High-Confidence Computing Pub Date : 2025-02-28 DOI: 10.1016/j.hcc.2025.100300

Biwei Yan , Kun Li , Minghui Xu , Yueyan Dong , Yue Zhang , Zhaochun Ren , Xiuzhen Cheng

{"title":"On protecting the data privacy of Large Language Models (LLMs) and LLM agents: A literature review","authors":"Biwei Yan , Kun Li , Minghui Xu , Yueyan Dong , Yue Zhang , Zhaochun Ren , Xiuzhen Cheng","doi":"10.1016/j.hcc.2025.100300","DOIUrl":"10.1016/j.hcc.2025.100300","url":null,"abstract":"<div><div>Large Language Models (LLMs) are complex artificial intelligence systems, which can understand, generate, and translate human languages. By analyzing large amounts of textual data, these models learn language patterns to perform tasks such as writing, conversation, and summarization. Agents built on LLMs (LLM agents) further extend these capabilities, allowing them to process user interactions and perform complex operations in diverse task environments. However, during the processing and generation of massive data, LLMs and LLM agents pose a risk of sensitive information leakage, potentially threatening data privacy. This paper aims to demonstrate data privacy issues associated with LLMs and LLM agents to facilitate a comprehensive understanding. Specifically, we conduct an in-depth survey about privacy threats, encompassing passive privacy leakage and active privacy attacks. Subsequently, we introduce the privacy protection mechanisms employed by LLMs and LLM agents and provide a detailed analysis of their effectiveness. Finally, we explore the privacy protection challenges for LLMs and LLM agents as well as outline potential directions for future developments in this domain.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 2","pages":"Article 100300"},"PeriodicalIF":3.2,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An insider threat detection method based on improved Test-Time Training model 一种基于改进Test-Time Training模型的内部威胁检测方法

IF 3.2

High-Confidence Computing Pub Date : 2025-01-14 DOI: 10.1016/j.hcc.2024.100283

Xiaoling Tao , Jianxiang Liu , Yuelin Yu , Haijing Zhang , Ying Huang

{"title":"An insider threat detection method based on improved Test-Time Training model","authors":"Xiaoling Tao , Jianxiang Liu , Yuelin Yu , Haijing Zhang , Ying Huang","doi":"10.1016/j.hcc.2024.100283","DOIUrl":"10.1016/j.hcc.2024.100283","url":null,"abstract":"<div><div>As network and information systems become widely adopted across industries, cybersecurity concerns have grown more prominent. Among these concerns, insider threats are considered particularly covert and destructive. Insider threats refer to malicious insiders exploiting privileged access to networks, systems, and data to intentionally compromise organizational security. Detecting these threats is challenging due to the complexity and variability of user behavior data, combined with the subtle and covert nature of insider actions. Traditional detection methods often fail to capture both long-term dependencies and short-term fluctuations in time-series data, which are crucial for identifying anomalous behaviors. To address these issues, this paper introduces the Test-Time Training (TTT) model for the first time in the field of insider threat detection, and proposes a detection method based on the TTT-ECA-ResNet model. First, the dataset is preprocessed. TTT is applied to extract long-term dependencies in features, effectively capturing dynamic sequence changes. The Residual Network, incorporating the Efficient Channel Attention mechanism, is used to extract local feature patterns, capturing relationships between different positions in time-series data. Finally, a Linear layer is employed for more precise detection of insider threats. The proposed approaches were evaluated using the CMU CERT Insider Threat Dataset, achieving an AUC of 98.75% and an F1-score of 96.81%. The experimental results demonstrate the effectiveness of the proposed methods, outperforming other state-of-the-art approaches.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 1","pages":"Article 100283"},"PeriodicalIF":3.2,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422030","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

Secure and trusted sharing mechanism of private data for Internet of Things 安全可信的物联网私有数据共享机制

IF 3.2

High-Confidence Computing Pub Date : 2024-12-24 DOI: 10.1016/j.hcc.2024.100273

Mengyuan Li , Shaoyong Guo , Wenjing Li , Ao Xiong , Xiaoming Zhou , Jun Qi , Feng Qi , Dong Wang , Da Li

{"title":"Secure and trusted sharing mechanism of private data for Internet of Things","authors":"Mengyuan Li , Shaoyong Guo , Wenjing Li , Ao Xiong , Xiaoming Zhou , Jun Qi , Feng Qi , Dong Wang , Da Li","doi":"10.1016/j.hcc.2024.100273","DOIUrl":"10.1016/j.hcc.2024.100273","url":null,"abstract":"<div><div>In recent years, the rapid development of Internet of Things (IoT) technology has led to a significant increase in the amount of data stored in the cloud. However, traditional IoT systems rely primarily on cloud data centers for information storage and user access control services. This practice creates the risk of privacy breaches on IoT data sharing platforms, including issues such as data tampering and data breaches. To address these concerns, blockchain technology, with its inherent properties such as tamper-proof and decentralization, has emerged as a promising solution that enables trusted sharing of IoT data. Still, there are challenges to implementing encrypted data search in this context. This paper proposes a novel searchable attribute cryptographic access control mechanism that facilitates trusted cloud data sharing. Users can use keywords To efficiently search for specific data and decrypt content keys when their properties are consistent with access policies. In this way, cloud service providers will not be able to access any data privacy-related information, ensuring the security and trustworthiness of data sharing, as well as the protection of user data privacy. Our simulation results show that our approach outperforms existing studies in terms of time overhead. Compared to traditional access control schemes,our approach reduces data encryption time by 33%, decryption time by 5%, and search time by 75%.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 2","pages":"Article 100273"},"PeriodicalIF":3.2,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental review Kubernetes应用程序在异构CPU架构上的性能基准测试：实验回顾

IF 3.2

High-Confidence Computing Pub Date : 2024-12-18 DOI: 10.1016/j.hcc.2024.100276

Jannatun Noor, MD Badsha Faysal, MD Sheikh Amin, Bushra Tabassum, Tamim Raiyan Khan, Tanvir Rahman

{"title":"Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental review","authors":"Jannatun Noor, MD Badsha Faysal, MD Sheikh Amin, Bushra Tabassum, Tamim Raiyan Khan, Tanvir Rahman","doi":"10.1016/j.hcc.2024.100276","DOIUrl":"10.1016/j.hcc.2024.100276","url":null,"abstract":"<div><div>With the rapid advancement of cloud technologies, cloud services have enormously contributed to the cloud community for application development life-cycle. In this context, Kubernetes has played a pivotal role as a cloud computing tool, enabling developers to adopt efficient and automated deployment strategies. Using Kubernetes as an orchestration tool and a cloud computing system as a manager of the infrastructures, developers can boost the development and deployment process. With cloud providers such as GCP, AWS, Azure, and Oracle offering Kubernetes services, the availability of both x86 and ARM platforms has become evident. However, while x86 currently dominates the market, ARM-based solutions have seen limited adoption, with only a few individuals actively working on ARM deployments. This study explores the efficiency and cost-effectiveness of implementing Kubernetes on different CPU platforms. By comparing the performance of x86 and ARM platforms, this research seeks to ascertain whether transitioning to ARM presents a more advantageous option for Kubernetes deployments. Through a comprehensive evaluation of scalability, cost, and overall performance, this study aims to shed light on the viability of leveraging ARM on different CPUs by providing valuable insights.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 1","pages":"Article 100276"},"PeriodicalIF":3.2,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403423","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

Erratum to “Exploring Personalized Internet of Things (PIoT), social connectivity, and Artificial Social Intelligence (ASI): A survey” [High-Confidence Computing 4 (2024) 100242] “探索个性化物联网（PIoT）、社会连接和人工社会智能（ASI）：一项调查”的勘误[高置信度计算4 (2024)100242]

IF 3.2

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

Three-dimensional dynamic gesture recognition method based on convolutional neural network 基于卷积神经网络的三维动态手势识别方法

IF 3.2

High-Confidence Computing Pub Date : 2024-11-06 DOI: 10.1016/j.hcc.2024.100280

Ji Xi , Weiqi Zhang , Zhe Xu , Saide Zhu , Linlin Tang , Li Zhao

{"title":"Three-dimensional dynamic gesture recognition method based on convolutional neural network","authors":"Ji Xi , Weiqi Zhang , Zhe Xu , Saide Zhu , Linlin Tang , Li Zhao","doi":"10.1016/j.hcc.2024.100280","DOIUrl":"10.1016/j.hcc.2024.100280","url":null,"abstract":"<div><div>With the rapid advancement of virtual reality, dynamic gesture recognition technology has become an indispensable and critical technique for users to achieve human–computer interaction in virtual environments. The recognition of dynamic gestures is a challenging task due to the high degree of freedom and the influence of individual differences and the change of gesture space. To solve the problem of low recognition accuracy of existing networks, an improved dynamic gesture recognition algorithm based on ResNeXt architecture is proposed. The algorithm employs three-dimensional convolution techniques to effectively capture the spatiotemporal features intrinsic to dynamic gestures. Additionally, to enhance the model’s focus and improve its accuracy in identifying dynamic gestures, a lightweight convolutional attention mechanism is introduced. This mechanism not only augments the model’s precision but also facilitates faster convergence during the training phase. In order to further optimize the performance of the model, a deep attention submodule is added to the convolutional attention mechanism module to strengthen the network’s capability in temporal feature extraction. Empirical evaluations on EgoGesture and NvGesture datasets show that the accuracy of the proposed model in dynamic gesture recognition reaches 95.03% and 86.21%, respectively. When operating in RGB mode, the accuracy reached 93.49% and 80.22%, respectively. These results underscore the effectiveness of the proposed algorithm in recognizing dynamic gestures with high accuracy, showcasing its potential for applications in advanced human–computer interaction systems.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 1","pages":"Article 100280"},"PeriodicalIF":3.2,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387521","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

Learning-based cooperative content caching and sharing for multi-layer vehicular networks 基于学习的多层车辆网络协同内容缓存与共享

IF 3.2

High-Confidence Computing Pub Date : 2024-11-05 DOI: 10.1016/j.hcc.2024.100277

Jun Shi , Yuanzhi Ni , Lin Cai , Zhuocheng Du

{"title":"Learning-based cooperative content caching and sharing for multi-layer vehicular networks","authors":"Jun Shi , Yuanzhi Ni , Lin Cai , Zhuocheng Du","doi":"10.1016/j.hcc.2024.100277","DOIUrl":"10.1016/j.hcc.2024.100277","url":null,"abstract":"<div><div>Caching and sharing the content files are critical and fundamental for various future vehicular applications. However, how to satisfy the content demands in a timely manner with limited storage is an open issue owing to the high mobility of vehicles and the unpredictable distribution of dynamic requests. To better serve the requests from the vehicles, a cache-enabled multi-layer architecture, consisting of a Micro Base Station (MBS) and several Small Base Stations (SBSs), is proposed in this paper. Considering that vehicles usually travel through the coverage of multiple SBSs in a short time period, the cooperative caching and sharing strategy is introduced, which can provide comprehensive and stable cache services to vehicles. In addition, since the content popularity profile is unknown, we model the content caching problems in a Multi-Armed Bandit (MAB) perspective to minimize the total delay while gradually estimating the popularity of content files. The reinforcement learning-based algorithms with a novel Q-value updating module are employed to update the caching files in different timescales for MBS and SBSs, respectively. Simulation results show the proposed algorithm outperforms benchmark algorithms with static or varying content popularity. In the high-speed environment, the cooperation between SBSs effectively improves the cache hit rate and further improves service performance.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 2","pages":"Article 100277"},"PeriodicalIF":3.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143917787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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

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

{"title":"A study on an efficient OSS inspection scheme based on encrypted GML","authors":"Seok-Joon Jang , Im-Yeong Lee , Daehee Seo , Su-Hyun Kim","doi":"10.1016/j.hcc.2024.100279","DOIUrl":"10.1016/j.hcc.2024.100279","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"5 2","pages":"Article 100279"},"PeriodicalIF":3.2,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0