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检索条件"机构=Key Laboratory of Data and Intelligent System Security"
1022 条 记 录,以下是841-850 订阅
排序:
TRUST: A Toolkit for TEE-Assisted Secure Outsourced Computation over Integers
arXiv
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arXiv 2024年
作者: Zhao, Bowen Li, Jiuhui Xu, Peiming Li, Xiaoguo Pei, Qingqi Shen, Yulong Guangzhou Institute of Technology Xidian University Guangzhou510555 China State Key Laboratory of Public Big Data Guizhou University Guiyang550025 China Electric Power Research Institute CSG Guangdong Guangzhou510663 China Guangdong Provincial Key Laboratory of Power System Network Security Guangdong Guangzhou510663 China The College of Computer Science Chongqing University Chongqing400044 China The State Key Laboratory of Integrated Service Networks Xidian University Xi’an710126 China
Secure outsourced computation (SOC) provides secure computing services by taking advantage of the computation power of cloud computing and the technology of privacy computing (e.g., homomorphic encryption). Expanding ... 详细信息
来源: 评论
Discovering communities of malapps on android-based mobile cyber-physical systems
arXiv
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arXiv 2018年
作者: Su, Dan Liu, Jiqiang Wang, Wei Wang, Xiaoyang Du, Xiaojiang Guizani, Mohsen Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing100044 China Dept. of Computer and Information Sciences Temple University PhiladelphiaPA19122 United States Dept. of Electrical and Computer Engineering University of Idaho MoscowID United States
Android-based devices like smartphones have become ideal mobile cyber-physical systems (MCPS) due to their powerful processors and variety of sensors. In recent years, an explosively and continuously growing number of... 详细信息
来源: 评论
Towards Demystifying Android Adware: dataset and Payload Location
Towards Demystifying Android Adware: Dataset and Payload Loc...
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IEEE/ACM International Conference on Automated Software Engineering - Workshops (ASE Workshops)
作者: Chao Wang Tianming Liu Yanjie Zhao Lin Zhang Xiaoning Du Li Li Haoyu Wang Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Monash University Clayton Australia Huazhong University of Science and Technology Wuhan China The National Computer Emergency Response Team/Coordination Center of China (CNCERT/CC) Beijing China Beihang University Beijing China
Adware represents a pervasive threat in the mobile ecosystem, yet its inherent characteristics have been largely overlooked by previous research. This work takes a crucial step towards demystifying Android adware. We ... 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
DAMPER: A Dual-Stage Medical Report Generation Framework with Coarse-Grained MeSH Alignment and Fine-Grained Hypergraph Matching
arXiv
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arXiv 2024年
作者: Huang, Xiaofei Chen, Wenting Liu, Jie Lu, Qisheng Luo, Xiaoling Shen, Linlin Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China
Medical report generation is crucial for clinical diagnosis and patient management, summarizing diagnoses and recommendations based on medical imaging. However, existing work often overlook the clinical pipeline invol... 详细信息
来源: 评论
Application Research of Vertical Federated Learning Technology in Banking Risk Control Model Strategy
Application Research of Vertical Federated Learning Technolo...
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IEEE International Conference on Big data and Cloud Computing (BdCloud)
作者: Yong Luo Zhi Lu Xiaofei Yin Songfeng Lu Yiting Weng Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China China Minsheng Banking Corp. Ltd. Beijing China Shenzhen Huazhong University of Science and Technology Research Institute Wuhan China Shu Lun Pan Beijing China
This study centers on the application of vertical federated learning technology in the context of Internet banking loans, with a particular focus on innovations in data privacy protection, risk control model algorithm...
来源: 评论
Detecting and Corrupting Convolution-based Unlearnable Examples
arXiv
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arXiv 2023年
作者: Li, Minghui Wang, Xianlong Yu, Zhifei Hu, Shengshan Zhou, Ziqi Zhang, Longling Zhang, Leo Yu School of Software Engineering Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia
Convolution-based unlearnable examples (UEs) employ class-wise multiplicative convolutional noise to training samples, severely compromising model performance. This fire-new type of UEs have successfully countered all... 详细信息
来源: 评论
ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection
arXiv
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arXiv 2023年
作者: He, Junwei Xu, Qianqian Jiang, Yangbangyan Wang, Zitai Huang, Qingming Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Engineering CAS Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China
Graph anomaly detection is crucial for identifying nodes that deviate from regular behavior within graphs, benefiting various domains such as fraud detection and social network. Although existing reconstruction-based ... 详细信息
来源: 评论
Efficient Federated Learning with Spike Neural Networks for Traffic Sign Recognition
arXiv
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arXiv 2022年
作者: Xie, Kan Zhang, Zhe Li, Bo Kang, Jiawen Niyato, Dusit Xie, Shengli Wu, Yi The School of Automation Guangdong University of Technology Guangzhou510006 China The Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China The Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China The 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou510006 China The Guangdong Key Laboratory of IoT Information Technology Guangzhou510006 China The School of Data Science and Technology Heilongjiang University Harbin150080 China The Institute for Cryptology & Network Security Heilongjiang University Harbin150080 China School of Computer Science and Engineering Nanyang Technological University Singapore
With the gradual popularization of self-driving, it is becoming increasingly important for vehicles to smartly make the right driving decisions and autonomously obey traffic rules by correctly recognizing traffic sign... 详细信息
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