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检索条件"机构=Shanghai Key Laboratory of Computer Software Evaluating and Testing"
329 条 记 录,以下是321-330 订阅
排序:
PIG: Prompt Images Guidance for Night-Time Scene Parsing
arXiv
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arXiv 2024年
作者: Xie, Zhifeng Qiu, Rui Wang, Sen Tan, Xin Xie, Yuan Ma, Lizhuang Department of Film and Television Engineering Shanghai University Shanghai200072 China Shanghai Key Laboratory of Computer Software Testing and Evaluating China Hanghai Engineering Research Center of Motion Picture Special Effects Shanghai200072 China School of Computer Science and Technology China Normal University Shanghai200062 China Chongqing Institute of East China Normal University Chongqing401120 China School of Computer Science and Technology East China Normal University Shanghai200062 China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China
Night-time scene parsing aims to extract pixel-level semantic information in night images, aiding downstream tasks in understanding scene object distribution. Due to limited labeled night image datasets, unsupervised ... 详细信息
来源: 评论
BRFL: A Blockchain-based Byzantine-Robust Federated Learning Model
arXiv
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arXiv 2023年
作者: Li, Yang Xia, Chunhe Li, Chang Wang, Tianbo The Key Laboratory of Beijing Network Technology Beihang University Beijing100191 China The Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing Guangxi Normal University Guilin541004 China The School of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou450000 China The School of Cyber Science and Technology Beihang University Beijing100191 China The Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai201112 China
With the increasing importance of machine learning, the privacy and security of training data have become critical. Federated learning, which stores data in distributed nodes and shares only model parameters, has gain... 详细信息
来源: 评论
FedDLM: A Fine-Grained Assessment Scheme for Risk of Sensitive Information Leakage in Federated Learning-based Android Malware Classifier
FedDLM: A Fine-Grained Assessment Scheme for Risk of Sensiti...
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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
作者: Changnan Jiang Chunhe Xia Chen Chen Huacheng Li Tianbo Wang Xiaojian Li Beijing Key Lab. of Network Technology Beihang University Beijing China Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing Guangxi Normal University Guilin China School of Cyber Science and Technology Beihang University Beijing China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China College of Computer Science and Information Technology Guangxi Normal University Guilin China
In the traditional centralized Android malware classification framework, privacy concerns arise as it requires collecting users’ app samples containing sensitive information directly. To address this problem, new cla... 详细信息
来源: 评论
HF-Mid: A Hybrid Framework of Network Intrusion Detection for Multi-type and Imbalanced Data
HF-Mid: A Hybrid Framework of Network Intrusion Detection fo...
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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
作者: Weidong Zhou Tianbo Wang Guotao Huang Xiaopeng Liang Chunhe Xia Xiaojian Li Beijing Key Lab. of Network Technology Beihang University Beijing China School of Cyber Science and Technology Beihang University Beijing China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing Guangxi Normal University Guilin China College of Computer Science and Information Technology Guangxi Normal University Guilin China
The data-driven deep learning methods have brought significant progress and potential to intrusion detection. However, there are two thorny problems caused by the characteristics of intrusion data: "multi-type fe... 详细信息
来源: 评论
FedDRC: A Robust Federated Learning-based Android Malware Classifier under Heterogeneous Distribution
FedDRC: A Robust Federated Learning-based Android Malware Cl...
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International Conference on computer Supported Cooperative Work in Design
作者: Changnan Jiang Chunhe Xia Mengyao Liu Chen Chen Huacheng Li Tianbo Wang Pengfei Li Beijing Key Lab. of Network Technology Beihang University Beijing China Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing Guangxi Normal University Guilin China School of Cyber Science and Technology Beihang University Beijing China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China SNationa Innovation Center of Intelligent and Connected Vehicles Beijing China
In the traditional centralized Android malware classification framework, privacy concerns exist due to collected users’ apps containing sensitive information. A new classification framework based on Federated Learnin... 详细信息
来源: 评论
An Optimization Method Based on Be-ACO Algorithm in Service Composition Context
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Computational intelligence and neuroscience 2022年 第1期2022卷 5231262页
作者: Zhoujie Du Huaikou Miao School of Computer Engineering and Science Shanghai University Shanghai 200444 China. Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai 201112 China.
With the increasing complexity of users' needs and increasing uncertainty of a single web service in big data environment, service composition becomes more and more difficult. In order to improve the solution accu...
来源: 评论
FedDADP: A Privacy-Risk-Adaptive Differential Privacy Protection Method for Federated Android Malware Classifier
FedDADP: A Privacy-Risk-Adaptive Differential Privacy Protec...
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International Joint Conference on Neural Networks (IJCNN)
作者: Changnan Jiang Chunhe Xia Mengyao Liu Rui Fang Pengfei Li Huacheng Li Tianbo Wang Beijing Key Lab. of Network Technology Beihang University Beijing China Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing Guangxi Normal University Guilin China School of Cyber Science and Technology Beihang University Beijing China SNationa Innovation Center of Intelligent and Connected Vehicles Beijing China Shanghai Key Laboratory of Computer Software Evaluating and Testing China
The federated Android malware classifier has attracted much attention owing to its advantages of privacy protection and multi-party joint modeling. However, the research indicates that the gradient transmitted within ... 详细信息
来源: 评论
Message from the InSTA 2022 chairs
Proceedings - 2022 IEEE 14th International Conference on Sof...
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Proceedings - 2022 IEEE 14th International Conference on software testing, Verification and Validation Workshops, ICSTW 2022 2022年 xvii页
作者: Masuda, Satoshi Nishi, Yasuharu Hagar, Jon Katayama, Tetsuro Liu, Qin Liu, Zhenyu Tsuda, Kazuhiko Yumoto, Tsuyoshi Takeda, T. Zhang, W. Hiruta, Y. Suhara, H. Masuda, S. Suzuki, K. Hagar, J. Tokyo City University Japan The University of Electro-Communications Japan Grand Software Testing United States University of Miyazaki Japan Tongji University China Shanghai Key Laboratory of Computer Software Testing and Evaluation China China University of Tsukuba Japan Japan Npo ASTER Japan Japan Software Bug Prediction Model Based on Mathematical Graph Features Metrics Japan Obtaining Fuzzing Results with Different Timeouts
来源: 评论
Test Case Generation for Web Application Based on Markov Reward Process
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Journal of Physics: Conference Series 2021年 第1期1792卷
作者: Jing Cao Xiaoqiang Liu Hui Guo Lizhi Cai Yun Hu College of Computer Science and Technology Donghua University Shanghai 201620 China Shanghai Key Laboratory of Computer Software Testing &Evaluation Shanghai 201112 China
Web applications often face continuous updating due to functional change or UI renew, while it remains a challenge to guarantee their correctness. The goal of software testing is to find defects in a limited time rang...
来源: 评论