检索结果-南通市图书馆

An efficient data aggregation scheme with local differential privacy in smart grid

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Digital Communications and Networks 2022年第3期8卷 333-342页

作者： Na Gai Kaiping Xue Bin Zhu Jiayu Yang Jianqing Liu Debiao He School of Cyber Science and Technology University of Science and Technology of ChinaHefeiAnhui230027China Department of Electronic Engineering and Information Science University of Science and Technology of ChinaHefeiAnhui230027China Department of Electrical and Computer Engineering University of Alabama in HuntsvilleHuntsvilleAL35899USA Key Laboratory of Aerospace Information Security and Trusted Computing of Ministry of Education School of Cyber Science and EngineeringWuhan UniversityWuhanBeihu430072China

By integrating the traditional power grid with information and communication technology, smart grid achieves dependable, efficient, and flexible grid data processing. The smart meters deployed on the user side of the smart grid collect the users' power usage data on a regular basis and upload it to the control center to complete the smart grid data acquisition. The control center can evaluate the supply and demand of the power grid through aggregated data from users and then dynamically adjust the power supply and price, etc. However, since the grid data collected from users may disclose the user's electricity usage habits and daily activities, privacy concern has become a critical issue in smart grid data aggregation. Most of the existing privacy-preserving data collection schemes for smart grid adopt homomorphic encryption or randomization techniques which are either impractical because of the high computation overhead or unrealistic for requiring a trusted third party.

关键词： Local differential privacy data aggregation Smart grid Privacy preserving

A fine-grained privacy protection data aggregation scheme for outsourcing smart grid

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 Computer Science 2023年第3期17卷 187-198页

作者： Hongyang LI Xinghua LI Qingfeng CHENG School of Cyber Engineering Xidian UniversityXi’an 710071China Strategic Support Force Information Engineering University Zhengzhou 450001China

Compared with the traditional power grid,smart grid involves many advanced technologies and ***,due to the rapid development of various network technologies,smart grid is facing the challenges of balancing privacy,security,efficiency,and *** the proposed scheme,we design a privacy protection scheme for outsourcing smart grid aided by fog computing,which supports fine-grained privacy-protected data aggregation based on user *** fog server matches the encrypted characteristics in the received message with the encrypted aggregation rules issued by the service ***,the service provider can get more fine-grained analysis data based on user *** from the existing outsourcing smart grid schemes,the proposed scheme can achieve real-time pricing on the premise of protecting user privacy and achieving system fault ***,experiment analyses demonstrate that the proposed scheme has less computation overhead and lower transmission delay than existing schemes.

关键词： smart grid data aggregation fine-grained privacy preservation real-time pricing

维普期刊数据库

An Efficient and Privacy-Preserving data aggregation Scheme Supporting Arbitrary Statistical Functions in IoT

在线全文

学校读者我要写书评

暂无评论

China Communications 2022年第6期19卷 91-104页

作者： Haihui Liu Jianwei Chen Liwei Lin Ayong Ye Chuan Huang College of Computer and Cyber Security Fujian Normal UniversityFuzhou 350117China Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Normal UniversityFuzhou 350117China School of Computer Science and Mathematics Fujian University of TechnologyFuzhou 350118China Digital Fujian Institute of Big data Security Technology Fujian Normal UniversityFuzhou 350117China

The Internet of Things(IoT)has profoundly impacted our lives and has greatly revolutionized our *** terminal devices in an IoT data aggregation application sense real-time data for the remote cloud server to achieve intelligent ***,the high frequency of collecting user data will raise people concerns about personal *** recent years,many privacy-preserving data aggregation schemes have been ***,most existing schemes cannot support either arbitrary aggregation functions,or dynamic user group management,or fault *** this paper,we propose an efficient and privacy-preserving data aggregation *** the scheme,we design a lightweight encryption method to protect the user privacy by using a ring topology and a random location *** this basis,the proposed scheme supports not only arbitrary aggregation functions,but also flexible dynamic user ***,the scheme achieves faulttolerant capabilities by utilizing a future data buffering *** analysis reveals that the scheme can achieve the desired security properties,and experimental evaluation results show the scheme's efficiency in terms of computational and communication overhead.

关键词： Internet of Things data aggregation privacy protection arbitrary aggregation functions

维普期刊数据库

An Energy-Efficient Mobile Agent-Based data aggregation Scheme for Wireless Body Area Networks

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第3期70卷 5929-5948页

作者： Gulzar Mehmood Muhammad Zahid Khan Muhammad Fayaz Mohammad Faisal Haseeb Ur Rahman Jeonghwan Gwak Department of Computer Science&Information Technology University of MalakandChakdara Dir Lower23021Pakistan Department of Computer Science University of Central AsiaNarynKyrgyzstan Department of Software Korea National University of TransportationChungju27469Korea Department of Biomedical Engineering Korea National University of TransportationChungju27469Korea Department of AI Robotics Engineering Korea National University of TransportationChungju27469Korea Department of IT and Energy Convergence(BK21 FOUR) Korea National University of TransportationChungju27469Korea

Due to the advancement in wireless technology and miniaturization,Wireless Body Area Networks(WBANs)have gained enormous popularity,having various applications,especially in the healthcare *** are intrinsically resource-constrained;therefore,they have specific design and development *** such highly desirable requirement is an energy-efficient and reliable data aggregation(DA)mechanism for *** efficient and reliableDAmay ultimately push the network to operate without much human intervention and further extend the network *** conventional client-serverDAparadigm becomes unsuitable and inefficient for WBANs when a large amount of data is generated in the ***,in most of the healthcare applications(patient’s critical conditions),it is highly important and required to send data as soon as possible;therefore,reliable data aggregation in WBANs is of great *** tackle the shortcomings of the client-serverDAparadigm,theMobile Agent-Basedmechanismproved to be a more workable *** aMobile Agent-Based mechanism,a taskspecific mobile agent(code)traverses to the intended sources to gather *** agents travel on a predefined path called itinerary;however,planning a suitable and reliable itinerary for a mobile agent is also a challenging issue *** paper presents a new Mobile Agent-Based DA scheme for WBANs,which is energy-efficient and ***,in the proposed scheme,the network is divided into clusters,and cluster-heads are ***,a mobile agent is generated from the base station to collect the required data from cluster *** the case,if any fault occurs in the existing itinerary,an alternate itinerary is planned in real-time without compromising the network *** our simulation-based validation,we have found that the proposed system delivers significantly improved fault-tolerance and reliability with energy-efficiency and extended network lifetime in WBANs.

关键词： WBANs mobile-agent data aggregation reliability

Hierarchical data aggregation with data Offloading Scheme for Fog Enabled IoT Environment

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第3期44卷 2033-2047页

作者： P.Nalayini R.Arun Prakash Department of Computer Science and Engineering Kings College of EngineeringPunalkulam613303TamilnaduIndia Department of Computer Science and Engineering University College of EngineeringAriyalur621704TamilnaduIndia

Fog computing is a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awareness Internet of Things(IoT)*** the emergence of IoT-based services,the industry of internet-based devices has *** number of these devices has raised from millions to billions,and it is expected to increase further in the near ***,additional challenges will be added to the traditional centralized cloud-based architecture as it will not be able to handle that growth and to support all connected devices in real-time without affecting the user *** data aggregation models for Fog enabled IoT environ-ments possess high computational complexity and communication ***-fore,in order to resolve the issues and improve the lifetime of the network,this study develops an effective hierarchical data aggregation with chaotic barnacles mating optimizer(HDAG-CBMO)*** HDAG-CBMO technique derives afitness function from many relational matrices,like residual energy,average distance to neighbors,and centroid degree of target ***,a chaotic theory based population initialization technique is derived for the optimal initial position of ***,a learning based data offloading method has been developed for reducing the response time to IoT user requests.A wide range of simulation analyses demonstrated that the HDAG-CBMO technique has resulted in balanced energy utilization and prolonged lifetime of the Fog assisted IoT networks.

关键词： Internet of things fog computing barnacles mating optimizer data offloading data aggregation

Discrete GWO Optimized data aggregation for Reducing Transmission Rate in IoT

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第3期44卷 1869-1880页

作者： S.Siamala Devi K.Venkatachalam Yunyoung Nam Mohamed Abouhawwash Department of Computer Science and Engineering Sri Krishna College of TechnologyCoimbatore641042India Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced *** diagnosis of many diseases will improve the patient *** cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things(IoT),Wireless Sensor Networks(WSN),Embedded systems,Deep learning approaches and Optimization and aggregation *** data generated through these technologies will demand the bandwidth,data rate,latency of the *** this proposed work,efficient discrete grey wolf optimization(DGWO)based data aggregation scheme using Elliptic curve Elgamal with Message Authentication code(ECEMAC)has been used to aggregate the parameters generated from the wearable sensor devices of the *** nodes that are far away from edge node will forward the data to its neighbor cluster head using *** scheme will reduce the number of transmissions over the *** aggregated data are preprocessed at edge node to remove the noise for better *** node will reduce the overhead of cloud *** aggregated data are forward to cloud server for central storage and *** proposed smart diagnosis will reduce the transmission cost through aggrega-tion scheme which will reduce the energy of the *** cost for proposed system for 300 nodes is 0.34μ*** energy cost of existing approaches such as secure privacy preserving data aggregation scheme(SPPDA),concealed data aggregation scheme for multiple application(CDAMA)and secure aggregation scheme(ASAS)are 1.3μJ,0.81μJ and 0.51μJ *** optimization approaches and encryption method will ensure the data privacy.

关键词： Discrete grey wolf optimization data aggregation cloud computing IoT WSN smart healthcare elliptic curve elgamal energy optimization

A Secret Confusion Based Energy-Saving and Privacy-Preserving data aggregation Algorithm

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2017年第4期26卷 740-746页

作者： ZHANG Jun ZHU Jianghao JIA Zongpu YAN Xixi College of Computer Science and Technology Henan Polytechnic University

To reduce communication overhead on the premise of privacy protection, this study presents a novel secret Confusion based energy-saving and privacypreserving data aggregation algorithm(CESPT). In confusion phase, CESPT confuses real sensory data and their sources by positive-negative pairs and a confusion factor is introduced to determine the quantity of pairs generated by a sensor, the exchange rounds and the threshold of data exchange, which affect communication overhead and privacy intensity of a Wireless sensor network(WSN). In aggregation phase, CESPT adopts a positive-negative neutralization strategy and a well-designed time slice allocation mechanism to reduce network traffic and message *** a word, CESPT can greatly reduce data traffic and energy consumption and obtain accurate statistical results on the basis of data privacy.

关键词： Wireless sensor network(WSN) data aggregation Privacy-preserving Energy-saving Positive negative pair

PVF-DA: Privacy-Preserving, Verifiable and FaultTolerant data aggregation in MEC

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

China Communications 2020年第8期17卷 58-69页

作者： Jianhong Zhang Qijia Zhang Shenglong Ji Wenle Bai School of Information Sciences and Technology North China University of TechnologyBeijing 100144China Guizhou University Guizhou Provincial Key Laboratory of Public Big DataGuiyang 550025China Legendsec Information Technology(Beijing)Inc. Beijing 100085China

As an emergent-architecture, mobile edge computing shifts cloud service to the edge of networks. It can satisfy several desirable characteristics for Io T systems. To reduce communication pressure from Io T devices, data aggregation is a good candidate. However, data processing in MEC may suffer from many challenges, such as unverifiability of aggregated data, privacy-violation and fault-tolerance. To address these challenges, we propose PVF-DA: privacy-preserving, verifiable and fault-tolerant data aggregation in MEC based on aggregator-oblivious encryption and zero-knowledge-proof. The proposed scheme can not only provide privacy protection of the reported data, but also resist the collusion between MEC server and corrupted Io T devices. Furthermore, the proposed scheme has two outstanding features: verifiability and strong fault-tolerance. Verifiability can make Io T device to verify whether the reported sensing data is correctly aggregated. Strong fault-tolerance makes the aggregator to compute an aggregate even if one or several Io Ts fail to report their data. Finally, the detailed security proofs are shown that the proposed scheme can achieve security and privacy-preservation properties in MEC.

关键词： MEC data aggregation verifiability privacy-preserving fault-tolerance

维普期刊数据库

A Differentially Private data aggregation Method Based on Worker Partition and Location Obfuscation for Mobile Crowdsensing

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2020年第4期63卷 223-241页

作者： Shuyu Li Guozheng Zhang School of Computer Science Shaanxi Normal UniversityXi’an710119China

With the popularity of sensor-rich mobile devices,mobile crowdsensing(MCS)has emerged as an effective method for data collection and ***,MCS platform usually need workers’precise locations for optimal task execution and collect sensing data from workers,which raises severe concerns of privacy *** to preserve workers’location and sensing data from the untrusted MCS platform,a differentially private data aggregation method based on worker partition and location obfuscation(DP-DAWL method)is proposed in the ***-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different privacy budget to the group according to group size(the number of workers).Then each worker’s location is obfuscated and his/her sensing data is perturbed by adding Laplace noise before uploading to the *** the stage of data aggregation,DP-DAWL method adopts an improved Kalman filter algorithm to filter out the added noise(including both added noise of sensing data and the system noise in the sensing process).Through using optimal estimation of noisy aggregated sensing data,the platform can finally gain better utility of aggregated data while preserving workers’*** experiments on the synthetic datasets demonstrate the effectiveness of the proposed method.

关键词： Mobile crowdsensing data aggregation differential privacy K-means kalman filter