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检索条件"机构=Cluster and Grid Computing Laboratory"
261 条 记 录,以下是251-260 订阅
排序:
Robin: A Novel Method to Produce Robust Interpreters for Deep Learning-Based Code Classifiers
arXiv
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arXiv 2023年
作者: Li, Zhen Zhang, Ruqian Zou, Deqing Wang, Ning Li, Yating Xu, Shouhuai Chen, Chen Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab China School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science University of Colorado Colorado Springs United States Center for Research in Computer Vision University of Central Florida United States School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China
Deep learning has been widely used in source code classification tasks, such as code classification according to their functionalities, code authorship attribution, and vulnerability detection. Unfortunately, the blac... 详细信息
来源: 评论
Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples
arXiv
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arXiv 2024年
作者: Zhou, Ziqi Li, Minghui Liu, Wei Hu, Shengshan Zhang, Yechao Wan, Wei Xue, Lulu Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab. China Cluster and Grid Computing Lab. China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia
With the evolution of self-supervised learning, the pre-training paradigm has emerged as a predominant solution within the deep learning landscape. Model providers furnish pre-trained encoders designed to function as ... 详细信息
来源: 评论
MISA: UNVEILING THE VULNERABILITIES IN SPLIT FEDERATED LEARNING
arXiv
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arXiv 2023年
作者: Wan, Wei Ning, Yuxuan Hu, Shengshan Xue, Lulu Li, Minghui Zhang, Leo Yu Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab China
Federated learning (FL) and split learning (SL) are prevailing distributed paradigms in recent years. They both enable shared global model training while keeping data localized on users' devices. The former excels...
来源: 评论
Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consistency
arXiv
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arXiv 2023年
作者: Liu, Xiaogeng Li, Minghui Wang, Haoyu Hu, Shengshan Ye, Dengpan Jin, Hai Wu, Libing Xiao, Chaowei School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab China School of Cyber Science and Engineering Wuhan University China Arizona State University United States
Deep neural networks are proven to be vulnerable to backdoor attacks. Detecting the trigger samples during the inference stage, i.e., the test-time trigger sample detection, can prevent the backdoor from being trigger... 详细信息
来源: 评论
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples
arXiv
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arXiv 2022年
作者: Hu, Shengshan Zhang, Junwei Liu, Wei Hou, Junhui Li, Minghui Zhang, Leo Yu Jin, Hai Sun, Lichao School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China Cluster and Grid Computing Lab China National Engineering Research Center for Big Data Technology and System Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China Services Computing Technology and System Lab China City University of Hong Kong Hong Kong Deakin University Australia Lehigh University United States
Point cloud completion, as the upstream procedure of 3D recognition and segmentation, has become an essential part of many tasks such as navigation and scene understanding. While various point cloud completion models ... 详细信息
来源: 评论
Downstream-agnostic Adversarial Examples
arXiv
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arXiv 2023年
作者: Zhou, Ziqi Hu, Shengshan Zhao, Ruizhi Wang, Qian Zhang, Leo Yu Hou, Junhui Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Wuhan University China School of Information and Communication Technology Griffith University Australia Department of Computer Science City University of Hong Kong Hong Kong National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab
Self-supervised learning usually uses a large amount of unlabeled data to pre-train an encoder which can be used as a general-purpose feature extractor, such that downstream users only need to perform fine-tuning oper... 详细信息
来源: 评论
The Power of Bamboo: On the Post-Compromise Security for Searchable Symmetric Encryption
arXiv
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arXiv 2024年
作者: Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands
Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studi... 详细信息
来源: 评论
基于污点和概率的逃逸恶意软件多路径探索
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Security and Safety 2023年 第3期2卷 83-106页
作者: 徐钫洲 张网 羌卫中 金海 National Engineering Research Center for Big Data Technology and System Wuhan 430074China Services Computing Technology and System Lab Cluster and Grid Computing LabWuhan 430074China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data SecurityWuhan 430074China School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Jinyinhu Laboratory Wuhan 430040China
Static analysis is often impeded by malware obfuscation techniques,such as encryption and packing,whereas dynamic analysis tends to be more resistant to obfuscation by leveraging concrete execution ***,malware can emp... 详细信息
来源: 评论
gECC: A GPU-based high-throughput framework for Elliptic Curve Cryptography
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ACM Transactions on Architecture and Code Optimization 1000年
作者: Qian Xiong Weiliang Ma Xuanhua Shi Yongluan Zhou Hai Jin Kaiyi Huang Haozhou Wang Zhengru Wang Huazhong University of Science and Technology Wuhan China School of Computer Huazhong University of Science and Technology Wuhan China University of Copenhagen Copenhagen Denmark School of computer science and technology Huazhong University of Science and Technology Services Computing Technology and System Laboratory / Cluster and Grid Computing Laboratory Wu hanwu China NVIDIA Corp Shanghai China
Elliptic Curve Cryptography (ECC) is an encryption method that provides security comparable to traditional techniques like Rivest–Shamir–Adleman (RSA) but with lower computational complexity and smaller key sizes, m... 详细信息
来源: 评论
高可扩展的RDF数据存储系统
高可扩展的RDF数据存储系统
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第29届中国数据库学术会议
作者: Yuan Pingpeng 袁平鹏 Liu Pu 刘谱 Zhang Wenya 张文娅 Wu Buwen 吴步文 Key Laboratory of Services Computing Technology and System(Huazhong University of Science and Technology) Ministry of Education Wuhan 430074 服务计算技术与系统教育部重点实验室(华中科技大学) 武汉430074 Key Laboratory of Cluster and Grid Computing of Hubei Province(Huazhong University of Science and Technology)Wuhan 430074 集群与网格计算湖北省重点实验室(华中科技大学) 武汉430074 School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 华中科技大学计算机科学与技术学院 武汉430074
由于资源描述框架(resource description framework,RDF)具有表达灵活、简洁等优点,已被接受为表达元数据及万维网上数据互联的规范.近年来,其数据量在以飞快的速度增长.相应地,要求存储RDF数据的系统应具有高扩展性.介绍了一个高可扩展... 详细信息
来源: 评论