检索结果-内蒙古大学图书馆

PriChain: Efficient Privacy-Preserving Fine-Grained Redactable Blockchains in Decentralized Settings

Chinese Journal of Electronics 2025年第1期34卷 82-97页

作者： Hongchen Guo Weilin Gan Mingyang Zhao Chuan Zhang Tong Wu Liehuang Zhu Jingfeng Xue School of Computer Science and Technology Beijing Institute of Technology School of Cyberspace Science and Technology Beijing Institute of Technology School of Computer and Communication Engineering University of Science and Technology Beijing

Recently, redactable blockchain has been proposed and leveraged in a wide range of real systems for its unique properties of decentralization, traceability, and transparency while ensuring controllable on-chain data redaction. However, the development of redactable blockchain is now obstructed by three limitations, which are data privacy breaches, high communication overhead, and low searching efficiency, respectively. In this paper, we propose PriChain, the first efficient privacy-preserving fine-grained redactable blockchain in decentralized settings. PriChain provides data owners with rights to control who can read and redact on-chain data while maintaining downward compatibility, ensuring the one who can redact will be able to read. Specifically, inspired by the concept of multi-authority attribute-based encryption, we utilize the isomorphism of the access control tree, realizing fine-grained redaction mechanism, downward compatibility, and collusion resistance. With the newly designed structure, PriChain can realize O（n） communication and storage overhead compared to prior O（n2） schemes. Furthermore, we integrate multiple access trees into a tree-based dictionary, optimizing searching efficiency. Theoretical analysis proves that PriChain is secure against the chosen-plaintext attack and has competitive complexity. The experimental evaluations show that PriChain realizes 10× efficiency improvement of searching and 100× lower communication and storage overhead on average compared with existing schemes.

关键词： Resistance Access control Data privacy Dictionaries Blockchains Encryption Complexity theory Usability Protection

来源：评论

学校读者我要写书评

暂无评论

Towards Reliable Configuration Management in Clouds: A Lightweight Consistency Validation Mechanism for Virtual Private Clouds

引用

Chinese Journal of Electronics 2025年第1期34卷 49-63页

作者： Yuhang Qiu Gongming Zhao Hongli Xu Long Li He Huang Liusheng Huang School of Computer Science and Technology University of Science and Technology of China Suzhou Institute for Advanced Research University of Science and Technology of China School of Computer Science and Technology Soochow University

The virtual private cloud service currently lacks a real-time end-to-end consistency validation mechanism, which prevents tenants from receiving immediate feedback on their requests. Existing solutions consume excessive communication and computational resources in such large-scale cloud environments, and suffer from poor timeliness. To address these issues, we propose a lightweight consistency validation mechanism that includes real-time incremental validation and periodic full-scale validation. The former leverages message layer aggregation to enable tenants to swiftly determine the success of their requests on hosts with minimal communication overhead. The latter utilizes lightweight validation checksums to compare the expected and actual states of hosts locally, while efficiently managing the checksums of various host entries using inverted indexing. This approach enables us to efficiently validate the complete local configurations within the limited memory of hosts. In summary, our proposed mechanism achieves closed-loop implementation for new requests and ensures their long-term effectiveness.

关键词： Cloud computing Memory management Configuration management Reliability engineering Real-time systems Indexing

来源：评论

学校读者我要写书评

暂无评论

LucIE: Language-guided local image editing for fashion images

引用

Computational Visual Media 2025年第1期11卷 179-194页

作者： Huanglu Wen Shaodi You Ying Fu School of Computer Science and Technology Beijing Institute of TechnologyBeijingChina Computer Vision Research Group in the Institute of Informatics University of AmsterdamAmsterdamthe Netherlands

Language-guided fashion image editing is challenging,as fashion image editing is local and requires high precision,while natural language cannot provide precise visual information for *** this paper,we propose LucIE,a novel unsupervised language-guided local image editing method for fashion *** adopts and modifies recent text-to-image synthesis network,DF-GAN,as its ***,the synthesis backbone often changes the global structure of the input image,making local image editing *** increase structural consistency between input and edited images,we propose Content-Preserving Fusion Module(CPFM).Different from existing fusion modules,CPFM prevents iterative refinement on visual feature maps and accumulates additive modifications on RGB *** achieves local image editing explicitly with language-guided image segmentation and maskguided image blending while only using image and text *** on the DeepFashion dataset shows that LucIE achieves state-of-the-art *** with previous methods,images generated by LucIE also exhibit fewer *** provide visualizations and perform ablation studies to validate LucIE and the *** also demonstrate and analyze limitations of LucIE,to provide a better understanding of LucIE.

关键词： deep learning language-guided image editing local image editing content preservation fashion images

来源：评论

学校读者我要写书评

暂无评论

Optimizing local search-based partial MaxSAT solving via initial assignment prediction

引用

Science China(Information Sciences) 2025年第2期68卷 59-73页

作者： Chanjuan LIU Guangyuan LIU Chuan LUO Shaowei CAI Zhendong LEI Wenjie ZHANG Yi CHU Guojing ZHANG School of Computer Science and Technology Dalian University of Technology School of Software Beihang University Institute of Software Chinese Academy of Sciences School of Computer Science Peking University

Partial maximum satisfiability(PMS) is a significant generalization of Boolean satisfiability(SAT) and maximum satisfiability(MaxSAT), by introducing hard clauses and soft clauses. Compared with SAT and MaxSAT, the PMS problem has more real-world applications where both hard and soft constraints are involved. Local search is an effective incomplete method for solving PMS and is useful for important domains where good-quality solutions are desired within reasonable *** local search PMS solvers, the approach for initial assignment generation is crucial because its effectiveness significantly affects practical performance. In this study, we propose a novel initial assignment prediction approach, called InitPMS. When predicting an assignment for PMS, InitPMS considers the specific structure of PMS instances, i.e., distinguishing hard and soft clauses. Our experiments on extensive PMS instances from MaxSAT evaluations(MSEs) 2020 and 2021 show that InitPMS significantly boosts the performance of five state-of-the-art local search PMS solvers, demonstrating its generality. In addition,our results indicate that incorporating InitPMS could improve the performance of one of the best incomplete PMS solvers in MaxSAT Evaluation 2021, indicating that InitPMS might help advance the state of the art in PMS solving.

关键词： MaxSAT local search initial assignment incomplete method assignment prediction

来源：评论

学校读者我要写书评

暂无评论

Algorithms for online fault tolerance server consolidation

引用

Digital Communications and Networks 2025年第2期11卷 514-523页

作者： Boyu Li Bin Wu Meng Shen Hao Peng Weisheng Li Hong Zhang Jie Gan Zhihong Tian Guangquan Xu College of Intelligence and Computing Tianjin University School of Cyberspace Science and Technology Beijing Institute of Technology School of Computer Science and Technology Zhejiang Normal University School of Computer Science and Technology Chongqing University of Posts and Telecommunications School of Astronautics Beihang University School of Computer Science University of Sydney Cyberspace Institute of Advanced Technology Guangzhou University

We study a novel replication mechanism to ensure service continuity against multiple simultaneous server failures. In this mechanism, each item represents a computing task and is replicated into ξ + 1 servers for some integer ξ ≥ 1, with workloads specified by the amount of required resources. If one or more servers fail, the affected workloads can be redirected to other servers that host replicas associated with the same item, such that the service is not interrupted by the failure of up to ξ servers. This requires that any feasible assignment algorithm must reserve some capacity in each server to accommodate the workload redirected from potential failed servers without overloading, and determining the optimal method for reserving capacity becomes a key issue. Unlike existing algorithms that assume that no two servers share replicas of more than one item, we first formulate capacity reservation for a general arbitrary scenario. Due to the combinatorial nature of this problem, finding the optimal solution is difficult. To this end, we propose a Generalized and Simple Calculating Reserved Capacity(GSCRC) algorithm, with a time complexity only related to the number of items packed in the server. In conjunction with GSCRC, we propose a robust replica packing algorithm with capacity optimization(RobustPack), which aims to minimize the number of servers hosting replicas and tolerate multiple server failures. Through theoretical analysis and experimental evaluations, we show that the RobustPack algorithm can achieve better performance.

关键词： Cloud computing Server consolidation Replica Fault tolerance

来源：评论

学校读者我要写书评

暂无评论

Secure Authentication in the Presence of Malicious Messages and Packet Reorders: Study on CAN Bus 15

Secure Authentication in the Presence of Malicious Messages ...

引用

15th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2025

作者： Maragkou, Sofia Grammatikakis, Miltos Papatheodorou, Nikos Jantsch, Axel Institute of Computer Technology Vienna University of Technology Vienna Austria Hellenic Mediterranean University Ece Dept. Heraklion Greece

ISBN: (纸本)9798331507695

Message authentication is fundamental for securing modern automotive networks. Our work focuses on integrating buffering in existing authentication protocols to sustain the presence of malicious or corrupt messages, and arbitrary packet swaps in the in-vehicle network. The proposed extension applies to the popular vatiCAN protocol, and other CAN bus authentication protocols, which use separate messages for transferring packet information and authentication data. The proposed extension uses one or more, independent Finite State Machines (FSMs) at each receiver node to temporarily store and subsequently validate message pairs, i.e., a legitimate data packet L with its hashed-based message authentication code (HMAC) packet H. The proposed methodology is evaluated experimentally on a Raspberry Pi-based Electronic Control Unit (ECU) with CAN interfaces. We examine key design parameters, such as the LH swap rate, the malicious rate, and queue configuration options, such as the queue size and flush policy. Results show that the protocol extension improves authentication. When the queue size is below 5, the LH swap rate is up to 50%, and 50% of malicious packets are introduced, the validated packet rate is low (5%). However, if the queue size exceeds 20, the verified packet rate reaches 100%, regardless of other parameters. The increased queue size has a minimal effect on latency, which increases by a few ms on average, and on false positives, which remain below 10-9. Statistical models help evaluate queue size bounds for worst-case scenarios, strengthening our experimental findings. © 2025 IEEE.

关键词： Authentication Protocol

来源：评论

学校读者我要写书评

暂无评论

Multi-label, Classification-based Prediction of Breast Cancer Metastasis Directions

IAENG International Journal of Computer Science

引用

IAENG International Journal of computer Science 2025年第1期52卷 1-10页

作者： Wang, Tingting Fan, Qi Tan, Liang Zhang, Beier School of Computer and Software Engineering Anhui Institute of Information Technology China School of Computer Science and Technology Huaibei Normal University China School of Computer and Software Engineering Anhui Institute of Information Technology China School of Computer Science and Technology Huaibei Normal University China

Predicting the metastatic direction of primary breast cancer (BC), thus assisting physicians in precise treatment, strict follow-up, and effectively improving the prognosis. The clinical data of 293,946 patients with primary BC diagnosed between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results database. Multiple interpolations and Multi-label Synthetic Minority Over-sampling Technique methods were used for data analysis, and machine learning model was established for multi-label classification. Finally, Surgical information, lymph node status, distant metastasis, tumor size, chemotherapy, histological type, and radiotherapy had significant influence as inputs. Compared with the k-nearest neighbor model, average accuracies of the decision tree and random forest (RF) models increased from 88.84% to 93.59% and 94.14%, respectively. Their average precision, recall rate, F1 score, area under the receiver operating characteristic curve and weighted-F1 increased from 87.24% to 95.85% and 94.74%, 87.73% to 90.40% and 91.76%, 87.07% to 92.16% and 93.45%, 97.11% to 99.53% and 99.95%, 82.13% to 89.44% and 90.48%, respectively. In conclusion, the RF model, which showed the best performance, can be used in multi-label prediction of BC metastasis directions, and can assist physicians in diagnosing and treating patients with primary BC. © (2025), (International Association of Engineers). All rights reserved.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based software engineering: progress,challenges, and opportunities

引用

Science China(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

来源：评论

学校读者我要写书评

暂无评论

Project-Based Learning Connecting Robotics and Artificial Intelligence 27th

Project-Based Learning Connecting Robotics and Artificial I...

引用

27th International Conference on Interactive Collaborative Learning, ICL 2024

作者： Posekany, Alexandra TU Vienna University of Technology Vienna Austria TGM – Vienna Institute of Technology Vienna Austria

ISBN: (纸本)9783031835223

The combination of knowledge and skill sets from robotics and Artificial Intelligence has proven as a powerful catalyst for students’ learning experiences, when applying available resources and knowledge acquired through vocational training. Within the Department of IT at an Austrian vocational high school, our students actively engage in projects that combine robotics and AI. Our diploma theses extend beyond mere classroom theory, allowing interested students to apply their knowledge in authentic, real-world scenarios in the form of thesis projects which span different engineering and IT disciplines. Our goal is to emphasize hands-on experiences and encourage our students to design, construct and program robots, even with the addition of AI technology, such as image recognition and classification trained for specific tasks. Through this practical immersion, our students gain a deeper understanding of robotics and AI, disciplines that are at the forefront of today’s technological innovation. We worked with two groups of students on interdisciplinary projects bridging the gap between robotics and AI and based on our students’ feedback found an increase in motivation to learn not only about the fields themselves, but also about related fields, from mathematical theory to better understand the intricate workings of AI algorithms to electronics and working with microcontrollers. Personal interviews with involved students have also pointed toward an increased motivation through the intense cooperation between the team members as well as the teachers responsible for supporting the project teams through their thesis projects. Projects connecting robotics and AI empower students to become adaptable, creative problem-solvers which is a crucial foundation for success in the twenty-first century. By fostering collaboration and critical thinking, while enhancing students’ technical skills and equipping them with the adaptability and creativity they require, this educational app

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Exploring the potential of residual mechanism in spiking neural networks for human action recognition

引用

Science China Technological Sciences 2025年第5期68卷 297-298页

作者： Jiaqi CHEN Ziliang REN Qieshi ZHANG Fuyong ZHANG Wenguo LIU School of Computer Science and Technology Dongguan University of Technology Shenzhen Institute of Advanced Technology Chinese Academy of Sciences The Chinese University of Hong Kong

Significant progress has been made in brain-computer science and technology through applying spiking neural networks(SNNs) [1]. More recently,due to its potential of processing complex spatio-temporal information,SNNs...

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：