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检索条件"任意字段=2nd International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering"

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A Secured Multiple Party Key Agreement Protocol Design Over cloud computing Platform by Using Statistical Data Analysis Logic

A Secured Multiple Party Key Agreement Protocol Design Over ...

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Sustainable computing and Smart Systems (ICSCSS), international conference on

作者： Allam Balaram Sajja Suneel P.M. Kavitha Achinta Saikia S. Gopi Y Dileep Kumar Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Department of CSE(Data Science) Institute of Aeronautical Engineering Dundigal Hyderabad Telangana India Department of Computer Science and Applications SRM Institute of Science And Technology Ramapuram Chennai-89 Department of Statistics Mariani College Mariani Jorhat Assam Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Department of ECE School of Engineering Mohan Babu University Tirupati

ISBN: (数字)9798350379990

ISBN: (纸本)9798350391558

In the field of cloud computing, ensuring secure and efficient key agreement among multiple parties has emerged as a paramount challenge. Traditional key agreement protocols often rely on central authorities or trusted third parties, posing significant security and privacy concerns. To address these challenges, this paper introduces a novel key agreement protocol designed specifically for cloud computing platforms, emphasizing security, efficiency, and resilience without depending on a trusted third party. The proposed protocol innovatively combines distributed Key Generation (DKG) with a Dynamic Consensus Mechanism, Zero-Knowledge Proof (ZKP) based authentication, and a Multi-cloud Redundancy approach, offering a comprehensive solution to secure multi-party communication in distributed cloud environments. The DKG protocol facilitates the collaborative generation of a shared secret among participants, significantly enhancing security by eliminating single points of failure. The proposed Dynamic Consensus Mechanism ensures the integrity and finality of key agreement transactions on a blockchain-based ledger, adapting to network conditions and participant trust levels to optimize performance without compromising security. ZKP-based authentication allows participants to verify their identities without revealing sensitive information, preserving privacy and thwarting impersonation attacks. Lastly, the Multi-cloud Redundancy strategy enhances the protocol's resilience to cloud-specific vulnerabilities and service outages, ensuring high availability and robustness.

关键词： cloud computing Privacy Redundancy Authentication Impersonation attacks Robustness Consensus protocol

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A study of dynamic characteristics of variable cross-section cantilever hollow cylinder under impact load 2

A study of dynamic characteristics of variable cross-section...

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2nd international conference on cloud computing and Mechatronic engineering, I3CME 2022

作者： Yang, Jie Zhang, Hui School of Civil Engineering Lanzhou Jiaotong University Gansu Lanzhou730070 China

ISBN: (纸本)9781510657502

A variable cross-section cantilever hollow cylinder is a special structure widely used in engineering. Based on the quasi-static limit analysis and impact dynamics, the dynamic characteristics of a cantilever hollow cylinder with a variable cross-section of constant thickness and variable thickness, under impact load, are studied respectively. The load position parameter and the plastic hinge position parameter are defined, and the conditions for determining the position of the plastic hinge are given based on the load position parameter. The expression of acceleration of the cantilever end and the control equation of the plastic hinge position parameter is derived from the momentum theorem and the moment of momentum theorem. According to the differential relationship between distributed inertial force and shear force and the differential relationship between shear force and bending moment, the expressions of shear force and bending moment are derived. The influence of the load position parameter on the plastic hinge position parameter and on the acceleration of the cantilever end, and the influence of the plastic hinge position parameter on the acceleration of the cantilever end are analyzed. The results of calculation examples show that when impact load obviously exceeds the static limit load of fixed end and the load position parameter μ is smaller than the critical load position parameter μic, the plastic hinge is located in the cylinder;the theoretical results of the acceleration of cantilever end ac and the plastic hinge position parameter λ are in good agreement with their numerical results;λ increases approximately linearly with μ;μ-ac relation curve and λ-ac relation curve are similar. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Acceleration

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Enhanced Multi-Objective Evolutionary Algorithm for Workflow Scheduling Problem 2

Enhanced Multi-Objective Evolutionary Algorithm for Workflow...

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2nd international conference on Advanced Algorithms and Signal Image Processing, AASIP 2022

作者： Lin, Chenxi Tian, Bin Wang, Zhen Zhou, Zhengbin School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Electronic Engineering Naval University of Engineering Wuhan China TROY Information Technology Co. Ltd Chengdu China

ISBN: (纸本)9781510660571

With the development and application of distributed cloud computing, the problem of assigning workflow tasks to computational resources has become more and more prominent. It involves multiple constraints and optimization objectives, and is a typical NP-hard problem. Existing evolutionary algorithms face local optimum and premature convergence problems. Considering these facts, we proposed a multi-objective evolutionary algorithm with elitism strategy (MOEAES) in this paper. To avoid local optimum, MOEAES uses a new crossover operator called Random Sub-Sequence Exchange Crossover (RSSEX), and it introduces a multi-population-based elitism strategy to accelerate the algorithm. Finally, experimental validation is carried out, which shows that MOEAES achieves performance improvement in terms of solution quality and convergence speed comparing to other methods. © 2022 SPIE.

关键词： Multiobjective optimization

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Offloading Methodologies for Energy consumption in Mobile Edge computing 2

Offloading Methodologies for Energy consumption in Mobile Ed...

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2nd international conference on Smart Electronics and Communication, ICOSEC 2021

作者： Saranya, G. Sasikala, E. SRM Institute of Science and Technology Department of Computer Science and Engineering Ramapuram Chennai India SRM Institute of Science and Technology Department of Computer Science and Engineering Kattankulathur Chennai India

ISBN: (纸本)9781665433686

Edge computing is a pioneering network that allows enterprises to clear out from the constraints exploited by standard cloud computing services. Despite the fact that public cloud continues to play a vital role in modern network engineering, the fascinating possibilities offered by Internet of Things devices, which can process information near the source, are prompting companies to rethink their IT services. This architecture was spawned by the fact that most devices near the edge lacked the processing power and storage space to analyze or process the data they collected. To overcome this issue, Offloading computations in MEC (mobile edge computing) is needed. Particularly, the types of offloading such as partial offloading, full offloading and distributed offloading may be applied to save energy and speed up the computation process. It includes various techniques like game theory approach, DNN based offloading etc. The computation offloading decision can be made based on tasks allocated for the processing to enhance results of the edge computing systems. The objective of this review will be improving the computation offloading where it will increase the operational performance of the edge devices to the greater extent. © 2021 IEEE.

关键词： computation offloading

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Multi-Task Scheduling Method for Information Security of Heterogeneous Big Data Networks Based on Artificial Intelligence Technology

Multi-Task Scheduling Method for Information Security of Het...

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Sensors, Electronics and Computer engineering (ICSECE), IEEE international conference on

作者： Yiping Chen Yingzi Zheng Department of Computer Science and Engineering Guangzhou Institute of Science and Technology Guangzhou China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

Multi-task scheduling of heterogeneous big data network information is proposed to improve the optimal configuration and application ability of network big data resources. A multi-task scheduling method of heterogeneous big data network information security based on artificial intelligence technology is proposed. A distributed storage and transmission structure model of heterogeneous big data is established under the task scheduling framework of cloud computing, and the heterogeneous mapping relationship is described according to the task submitted by users and the network information distribution between virtual machines. This paper establishes a scheduling channel between virtual machines and hosts, reasonably places and migrates heterogeneous big data network information to suitable hosts through artificial intelligence technology, and realizes reasonable allocation of computing resources and multi-task scheduling by using weighted polling scheduling method, so as to realize load-balanced scheduling of heterogeneous network information. The simulation results show that this method has good load balance in information task scheduling of heterogeneous big data networks, and the scheduling method has excellent global search and parallel search capabilities, which can adapt to large-scale information optimization of heterogeneous big data networks.

关键词： Processor scheduling Simulation Information security Big Data Multitasking Data models Resource management Artificial intelligence Optimization Load modeling

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Two-Factor distributed Authentication Scheme for cloud Storage

Two-Factor Distributed Authentication Scheme for Cloud Stora...

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international conference on Computers, Communications, and Systems (ICCCS)

作者： Yunxia Han Chunxiang Xu Shanshan Li Jingjie Lu School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Information Engineering Zhongnan University of Economics and Law Wuhan China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

distributed authentication plays a crucial role in cloud storage, requiring users to authenticate their identity to a set of key management servers. This process guarantees that only authenticated users gain access to cryptographic keys stored in these servers for decrypting outsourced data. How-ever, existing distributed authentication schemes rely solely on passwords, posing a critical weakness due to the recent surge in password-based attacks. Once passwords are compromised, adversaries can impersonate users, gaining unauthorized access to key management servers and acquiring cryptographic keys. To address this vulnerability, a recent multi-factor scheme has been proposed that introduces a distributed authentication mechanism for each popular factor such as passwords, Universal 2nd Factor (U2F), and email. Users could select multiple factors and utilize their corresponding mechanisms when authenticating to servers. Nevertheless, a simple combination of these authentication mechanisms incurs substantial overheads. In this paper, we propose a combined verification mechanism for passwords and U2F, allowing servers to efficiently verify both factors. Based on the mechanism, we present a two-factor distributed authentication for cloud storage, dubbed TDAC. In TDAC, users could authenticate to key management servers through a single password entry and a touch on their U2F. Experiments show that TDAC is efficient in terms of computation and communication overhead.

关键词： cloud computing Costs Communication systems Authentication Passwords Multi-party computation Computational efficiency

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cloud-Enabled Isolation Forest for Anomaly Detection in UAV-Based Power Line Inspection

Cloud-Enabled Isolation Forest for Anomaly Detection in UAV-...

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Networking and Communications (ICNWC), international conference on

作者： Jayabharathi Ramasamy E. Srividhya V. Vaidehi S. Vimaladevi N. Mohankumar S. Murugan Department of Computer Science and Engineering RMK College of Engineering and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Department of Computer Science Vinayaka Mission's Kirupananda Variyar Arts and Science College Vinayaka Mission's Research Foundation (DU) Salem Tamil Nadu India Department of Commerce and Business Administration School of Management Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering B.V. Raju Institute of Technology Telangana India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

ISBN: (数字)9798350365269

ISBN: (纸本)9798350365276

Unmanned Aerial Vehicles (UAVs) gather data efficiently for power line inspection. Anomaly detection is essential for power infrastructure dependability and security. It proposes a cloud-Enabled Isolation Forest (CEIF) method for UAV-based power line inspection. It improves the isolation forest algorithm's efficiency and scalability in cloud computing. It can process huge UAV inspection datasets by dispersing cloud computing. The technique, which effectively isolates anomalies, is applied to the cloud for fast power line inspection and anomaly identification. It describes the CEIF system's cloud service integration and distributed computing algorithm optimization. Real-world UAV-based power line inspection datasets show it can accurately detect abnormalities with low false-positive rates. It is scalable and robust for improving power infrastructure dependability and security. It allows cloud services to deploy real-world settings to implement different inspection scales.

关键词： cloud computing Scalability Forestry Inspection Autonomous aerial vehicles Sensors Security

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Preserving Patient Privacy in IoT Based Breast Cancer Monitoring System

Preserving Patient Privacy in IoT Based Breast Cancer Monito...

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international conference on Edge computing and Applications (ICECAA)

作者： Meenakshiammal R Bharathi R P. Krishnakumar Dept of CSE AP Rohini College of Engineering & Technology Kanyakumari India Dept of ECE AP University College of Engineering Nagercoil India Dept of CSE AP Amrita College of Engineering Erachakulam India

Disease detection plays a crucial role in providing right treatment to the patients. Currently, the lack of information on cancer prevention and awareness results in high fatality. Breast cancer is the second most deadliest disease across the globe. This type of cancer affects women than men. The proposed model employs an Internet of Things (IoT) based hand held device to predict breast cancer and transmit the heathcare data over the cloud for further medical analysis. The confidentiality of the patient's information is likely to be compromised during transmission. The patient's personal information might be intercepted by an outside party. Hence, the proposed model encrypts sensitive information using a mix of the Triple DES and AES method before sending it to the cloud. To improve the classification performance of MLP and SVM, Particle Swarm Optimization (PSO) is used, and a grid-based search was also used to determine the optimal settings of CNN and ANN models. To put the strategy to test, researchers used the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. The proposed model has achieved 98.5% accuracy in CNN classification and 99.2 % accuracy in ANN classification.

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Performance Optimization in distributed Multi-Agent Reinforcement Learning on cloud-Based Platforms

Performance Optimization in Distributed Multi-Agent Reinforc...

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international conference on computing and Networking Technology (ICCNT)

作者： Binod Kumar Choudhary Deepak Kumar Seema Sambargi Department of Electrical & Electronics Engineering ARKA JAIN University Jamshedpur Jharkhand India Department of Mathematics Vivekananda Global University Jaipur India Department of Management School of Management - UG JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Dispensed multi-agent reinforcement learning (MARL) is an effective tool for tackling tough manage troubles by means of allowing coordination and cooperation among multiple agents. In cloud-based platforms, MARL can benefit from the availability of compute resources for education, but they face precise scalability and optimization-demanding situations. In this paper, we endorse a collection of methods for improving the overall performance of disbursed MARL in cloud-primarily based structures. We attention on two elements of overall performance optimization for scaling out distributed MARL: implementation optimization and optimization across a couple of stages of education. First, we advocate numerous strategies for enhancing the implementation of dispensed MARL, which include optimizing reminiscence usage and introducing size-aware optimizers. 2nd, we propose methods of optimizing allotted MARL across one-of-a-kind phases of education, inclusive of optimization for hyper parameter selection and optimizing education convergence. Our experiments display that our proposed methods improve the performance of distributed MARL in cloud-primarily based platforms, leading to higher scalability and quicker mastering.

关键词： Fault tolerance Scalability Education Fault tolerant systems Reinforcement learning Optimization Programming profession Faces Convergence

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A Review Paper on cloud computing

A Review Paper on Cloud Computing

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international conference on Innovative Sustainable Computational Technologies (CISCT)

作者： Neeraj Singla Chahat Nisha Harnoor Chitkara University Institute of ETE Rajpura India

ISBN: (纸本)9781665474177

cloud computing has taken its place all over the IT industries. It is an on-demand internet-based computing service that provides the maximum result with minimum resources cloud computing provides a service that does not require any physical close to the computer hardware. cloud computing is a product of grid, distributed, parallel, and ubiquitous computing. This paper introduces the concepts, history pros, and cons of cloud computing. Now coming to IoT, it can be any device equipment, or object which connects us with the cloud using the internet or with another device that is connected. It has sensors, processing ability, software, and many technologies which can be used to share and fetch data or information with other devices and servers over the internet. Nowadays big companies are using cloud services for storing their data because it is easy to manage their data easily without any additional costs. cloud computing provides us the flexibility to play with our data and gives us more freedom with storage, access, and management. In this paper, we will see the advantages and disadvantages of using the cloud, how IoT is useful in cloud systems, and how we can overcome the problems related to the cloud.

关键词： Industries Performance evaluation cloud computing Software as a service Ubiquitous computing Hardware Sensors

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