检索结果-南通市图书馆

维普期刊数据库

SwiftTheft: A Time-Efficient Model Extraction Attack Framework Against Cloud-Based Deep Neural Networks

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2024年第1期33卷 90-100页

作者： Wenbin YANG Xueluan GONG Yanjiao CHEN Qian WANG Jianshuo DONG School of Cyber science and engineering Wuhan University School of computer science Wuhan University College of Electrical engineering Zhejiang University

With the rise of artificial intelligence and cloud computing, machine-learning-as-a-service platforms,such as Google, Amazon, and IBM, have emerged to provide sophisticated tasks for cloud applications. These proprietary models are vulnerable to model extraction attacks due to their commercial value. In this paper, we propose a time-efficient model extraction attack framework called Swift Theft that aims to steal the functionality of cloud-based deep neural network models. We distinguish Swift Theft from the existing works with a novel distribution estimation algorithm and reference model settings, finding the most informative query samples without querying the victim model. The selected query samples can be applied to various cloud models with a one-time selection. We evaluate our proposed method through extensive experiments on three victim models and six datasets, with up to 16 models for each dataset. Compared to the existing attacks, Swift Theft increases agreement(i.e., similarity) by 8% while consuming 98% less selecting time.

关键词： Performance evaluation Cloud computing Analytical models Computational modeling Estimation Artificial neural networks Artificial intelligence

WebFLex:A Framework for Web Browsers-Based Peer-to-Peer Federated Learning Systems Using WebRTC

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第3期78卷 4177-4204页

作者： Mai Alzamel Hamza Ali Rizvi Najwa Altwaijry Isra Al-Turaiki Department of computer science College of Computer and Information SciencesKing Saud UniversityRiyadhKingdom of Saudi Arabia Department of computer science and engineering Punjab Engineering CollegeChandigarhIndia

Scalability and information personal privacy are vital for training and deploying large-scale deep learning *** learning trains models on exclusive information by aggregating weights from various devices and taking advantage of the device-agnostic environment of web ***,relying on a main central server for internet browser-based federated systems can prohibit scalability and interfere with the training process as a result of growing client ***,information relating to the training dataset can possibly be extracted from the distributed weights,potentially reducing the privacy of the local data used for *** this research paper,we aim to investigate the challenges of scalability and data privacy to increase the efficiency of distributed training *** a result,we propose a web-federated learning exchange(WebFLex)framework,which intends to improve the decentralization of the federated learning *** is additionally developed to secure distributed and scalable federated learning systems that operate in web browsers across heterogeneous ***,WebFLex utilizes peer-to-peer interactions and secure weight exchanges utilizing browser-to-browser web real-time communication(WebRTC),efficiently preventing the need for a main central *** has actually been measured in various setups using the MNIST *** results show WebFLex’s ability to improve the scalability of federated learning systems,allowing a smooth increase in the number of participating devices without central data *** addition,WebFLex can maintain a durable federated learning procedure even when faced with device disconnections and network ***,it improves data privacy by utilizing artificial noise,which accomplishes an appropriate balance between accuracy and privacy preservation.

关键词： Federated learning web browser privacy deep learning

On optimal streaming kernelization algorithms

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

science China(Information sciences) 2024年第8期67卷 337-338页

作者： Hao FENG Wei YANG Jianer CHEN School of computer science Guangzhou University Department of computer science and engineering Texas A&M University

The streaming model has been a popular model in big data computation. Streaming kernelization algorithms can be regarded as data compression processes on streaming data. In this study, we give a general method for developing computational lower bounds for streaming kernelization algorithms that is applicable to a large class of computational problems. As an example, we use the method to prove computational lower bounds for the well-known problem d-Hi TTin GSET.

关键词：

DNACDS:Cloud IoE big data security and accessing scheme based on DNA cryptography

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Frontiers of computer science 2024年第1期18卷 157-170页

作者： Ashish SINGH Abhinav KUMAR Suyel NAMASUDRA School of computer engineering KIIT Deemed to be UniversityBhubaneshwar 751024India Department of computer science and engineering Indian Institute of Information Technology SuratSurat 394190India Department of computer science and engineering National Institute of Technology AgartalaAgartala 799046India

The Internet of Everything(IoE)based cloud computing is one of the most prominent areas in the digital big data *** approach allows efficient infrastructure to store and access big real-time data and smart IoE services from the *** IoE-based cloud computing services are located at remote locations without the control of the data *** data owners mostly depend on the untrusted Cloud Service Provider(CSP)and do not know the implemented security *** lack of knowledge about security capabilities and control over data raises several security *** Acid(DNA)computing is a biological concept that can improve the security of IoE big *** IoE big data security scheme consists of the Station-to-Station Key Agreement Protocol(StS KAP)and Feistel cipher *** paper proposed a DNA-based cryptographic scheme and access control model(DNACDS)to solve IoE big data security and access *** experimental results illustrated that DNACDS performs better than other DNA-based security *** theoretical security analysis of the DNACDS shows better resistance capabilities.

关键词： IoE based cloud computing DNA cryptography IoE big data security StS KAP feistel cipher IoE big data access

Cooperative control for heterogeneous multi-agent systems: progress, applications, and challenges

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

science China(Information sciences) 2024年第5期67卷 318-320页

作者： Bing YAN Peng SHI Jonathon CHAMBERS School of Electrical and Mechanical engineering Faculty of Science Engineering and TechnologyThe University of Adelaide School of engineering College of Science and Engineering University of Leicester

Cooperative control for heterogeneous multi-agent systems(MASs) is a critical and rapidly evolving field in modern automation and robotics. Characterized by the integration of agents with diverse capabilities and func... 详细信息

关键词： Multi agent systems

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第5期79卷 3067-3087页

作者： Arnab Dey Samit Biswas Dac-Nhuong Le Department of computer science and Technology Indian Institute of Engineering Science and TechnologyShibpurHowrah711103India faculty of Information Technology Haiphong UniversityHaiphong180000Vietnam

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd datas

关键词： Workout action recognition video stream action recognition residual network GRU attention

Highly efficient recovery of waste LiNi_(x)Co_(y)Mn_(z)O_(2) cathode materials using a process involving pyrometallurgy and hydrometallurgy

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Environmental science & engineering 2024年第2期18卷 149-160页

作者： Tianwei Zhang Juanye Dao Jinsong Wang Yuzhong Guo Rundong Wan Chengping Li Xian Zhou Zhengfu Zhang faculty of Materials science and engineering Kunming University of Science and TechnologyKunming 650093China

Substantial environmental and economic benefits can be achieved by recycling used lithium-ion batteries. Hydrometallurgy is often employed to recover waste LiNi_(x)Co_(y)Mn_(z)O_(2) cathode materials. As Ni, Co and Mn are transition metals, they exhibit similar properties;therefore, separating them is difficult. Thus, most researchers have focused on leaching processes, while minimal attention has been devoted to the separation of valuable metals from waste LiNi_(x)Co_(y)Mn_(z)O_(2) cathode materials. Herein, we propose an environment-friendly, gentle process involving the usage of pyrometallurgy and hydrometallurgy to gradually leach valuable metals and effectively separate them. Interestingly, Li is recovered through a reduction roasting and water leaching process using natural graphite powder, Ni and Co are recovered through ammonia leaching and extraction processes and Mn is recovered through acid leaching and evaporation–crystallization processes. Results show that ~87% Li, 97.01% Co, 97.08% Ni and 99% Mn can be leached using water, ammonia and acid leaching processes. The result obtained using the response surface methodology shows that the concentration of (NH4)2SO3 is a notable factor affecting the leaching of transition metals. Under optimal conditions, ~97.01% Co, 97.08% Ni and 0.64% Mn can be leached out. The decomposition of LiNi_(x)Co_(y)Mn_(z)O_(2) is a two-step process. This study provides valuable insights to develop an environment-friendly, gentle leaching process for efficiently recycling valuable metals, which is vital for the lithium-ion battery recycling industry.

关键词： Waste LiNixCoyMnzO2 cathode materials Leaching Effective separation Series process

Microstructures and Properties of Biomedical Mg-Zn-Sn-Zr Rolled Alloys

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Wuhan University of Technology(Materials science) 2024年第3期39卷 766-773页

作者：周生刚 ZHANG Daxin XU Yang DUAN Jihao LI Tao LIU Junfeng WANG Peng 曹勇 faculty of Material science and engineering Kunming University of Science and TechnologyKunming 650093China

The as-cast Mg-2.0Zn-1.5Sn-xZr(x=0,0.4,0.6,0.8,1.0 wt%)alloy was rolled with the pressure less than 5%each *** microstructure,mechanical properties,corrosion properties and biocompatibility of the alloy were *** microstructure of the alloy was observed and analyzed by scanning electron microscope,and the tensile test was carried out by universal tensile *** corrosion resistance of the alloy in Hank's solution was studied by hydrogen evolution experiment and electrochemical test,and the biocompatibility of the alloy was tested by L929 *** results show that Mg-2Zn-1.5Sn-xZr alloy has excellent mechanical *** elongation of Mg-2Zn-1.5Sn-xZr alloy decreases with the increase of Zr content,but the tensile strength first increases and then decreases with the increase of Zr *** the Zr content is 0.8 wt%,the maximum tensile strength of the alloy is 235 *** results of hydrogen evolution experiment and electrochemical analysis show that the corrosion resistance of the alloy is the best when the Zr content is 0.8 wt%,and all the five alloys have high *** conclusion,the rolled alloy has good properties and has broad application prospects in the field of biomaterials.

关键词： magnesium alloy corrosion performance mechanical properties biocompatibility

维普期刊数据库

Highly enhanced thermoelectric and mechanical performance of copper sulfides via natural mineral in-situ phase separation

在线全文

学校读者我要写书评

暂无评论

Journal of Advanced Ceramics 2024年第5期13卷 641-651页

作者： Xi Yan Hongjiang Pan Yixin Zhang Tianyu Yang Yangwei Wang Kun Huang Chongyu Wang Jing Feng Zhenhua Ge faculty of Materials science and engineering Kunming University of Science and TechnologyKunming 650093China

In situ phase separation precipitates play an important role in enhancing the thermoelectric properties of copper sulfides by suppressing phonon *** this study,Cu1.8S composites were fabricated by melting reactions and spark plasma *** complex structures,namely,micron-PbS,Sb_(2)S_(3),nano-FeS,and multiscale pores,originate from the introduction of FePb_(4)Sb_(6)S_(14)into the Cu1.8S *** effective element(Fe)doping and multiscale precipitates,the Cu_(1.8)S+0.5 wt%FePb_(4)Sb_(6)S_(14)bulk composite reached a high dimensionless figure of merit(ZT)value of 1.1 at 773 ***,the modulus obtained for this sample was approximately 40.27 GPa,which was higher than that of the pristine *** study provides a novel strategy for realizing heterovalent doping while forming various precipitates via in situ phase separation by natural minerals,which has been proven to be effective in improving the thermoelectric and mechanical performance of copper sulfides and is worth promoting in other thermoelectric systems.

关键词： in situ precipitates jamesonite natural mineral thermoelectric copper sulfides