Cloud computing provisions and allocates resources, in advance or real-time, to dynamic applications planned for execution. This is a challenging task as the Cloud-Service-Providers (CSPs) may not have sufficient resources at all times to satisfy the resource requests of the Cloud-Service-Users (CSUs). Further, the CSPs and CSUs have conflicting interests and may have different utilities. Service-Level-Agreement (SLA) negotiations among CSPs and CSUs can address these limitations. User Agents (UAs) negotiate for resources on behalf of the CSUs and help reduce the overall costs for the CSUs and enhance the resource utilization for the CSPs. This research proposes a broker-based mediation framework to optimize the SLA negotiation strategies between UAs and CSPs in Cloud environment. The impact of the proposed framework on utility, negotiation time, and request satisfaction are evaluated. The empirical results show that these strategies favor cooperative negotiation and achieve significantly higher utilities, higher satisfaction, and faster negotiation speed for all the entities involved in the negotiation.
{"title":"Broker-based optimization of SLA negotiations in cloud computing","authors":"P. Bharti, R. Ranjan, B. Prasad","doi":"10.3233/mgs-210349","DOIUrl":"https://doi.org/10.3233/mgs-210349","url":null,"abstract":"Cloud computing provisions and allocates resources, in advance or real-time, to dynamic applications planned for execution. This is a challenging task as the Cloud-Service-Providers (CSPs) may not have sufficient resources at all times to satisfy the resource requests of the Cloud-Service-Users (CSUs). Further, the CSPs and CSUs have conflicting interests and may have different utilities. Service-Level-Agreement (SLA) negotiations among CSPs and CSUs can address these limitations. User Agents (UAs) negotiate for resources on behalf of the CSUs and help reduce the overall costs for the CSUs and enhance the resource utilization for the CSPs. This research proposes a broker-based mediation framework to optimize the SLA negotiation strategies between UAs and CSPs in Cloud environment. The impact of the proposed framework on utility, negotiation time, and request satisfaction are evaluated. The empirical results show that these strategies favor cooperative negotiation and achieve significantly higher utilities, higher satisfaction, and faster negotiation speed for all the entities involved in the negotiation.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"30 1","pages":"179-195"},"PeriodicalIF":0.7,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81545142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the present study, the research problem concerns business intelligence, more precisely collaborative decision-making. The authors propose a complete modeling of a multi-agent active environment for the design of a multicriteria group decision support system dedicated to the spatial problem of localization in territory planning. The proposed model is called ActiveGDSS (Active Group Decision Support System) which uses a coupling between a geographic information system and a multi agents system and is endowed by a new negotiation protocol based on the concession allowing reaching to a consensus which satisfies the territorial actors. The main purpose is to integrate the principle of contextual activation in the modeling of the system which makes the environment an active entity. The main advantages of contextual activation are efficiency gain in terms of execution, better flexibility and reuse of agent behaviors.
在本研究中，研究的问题是商业智能，更确切地说，是协同决策。作者提出了一个完整的多智能体活动环境模型，用于设计一个多准则群体决策支持系统，以解决领土规划中的空间定位问题。该模型利用地理信息系统与多智能体系统之间的耦合，并赋予基于让步的协商协议，使其能够达成满足区域行为体的共识，称为ActiveGDSS (Active Group Decision Support System)。其主要目的是在系统建模中集成上下文激活原理，使环境成为一个活动实体。上下文激活的主要优点是在执行方面的效率提高，更好的灵活性和代理行为的重用。
{"title":"Modeling of an active multi-agent environment for the design of a multi-criteria group decision support system","authors":"Amel Kahina Nemdili, D. Hamdadou","doi":"10.3233/MGS-210344","DOIUrl":"https://doi.org/10.3233/MGS-210344","url":null,"abstract":"In the present study, the research problem concerns business intelligence, more precisely collaborative decision-making. The authors propose a complete modeling of a multi-agent active environment for the design of a multicriteria group decision support system dedicated to the spatial problem of localization in territory planning. The proposed model is called ActiveGDSS (Active Group Decision Support System) which uses a coupling between a geographic information system and a multi agents system and is endowed by a new negotiation protocol based on the concession allowing reaching to a consensus which satisfies the territorial actors. The main purpose is to integrate the principle of contextual activation in the modeling of the system which makes the environment an active entity. The main advantages of contextual activation are efficiency gain in terms of execution, better flexibility and reuse of agent behaviors.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"45 1","pages":"83-111"},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80601203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Energy production and consumption are one of the largest sources of greenhouse gases (GHG), along with industry, and is one of the highest causes of global warming. Forecasting the environmental cost of energy production is necessary for better decision making and easing the switch to cleaner energy systems in order to reduce air pollution. This paper describes a hybrid approach based on Artificial Neural Networks (ANN) and an agent-based architecture for forecasting carbon dioxide (CO2) issued from different energy sources in the city of Annaba using real data. The system consists of multiple autonomous agents, divided into two types: firstly, forecasting agents, which forecast the production of a particular type of energy using the ANN models; secondly, core agents that perform other essential functionalities such as calculating the equivalent CO2 emissions and controlling the simulation. The development is based on Algerian gas and electricity data provided by the national energy company. The simulation consists firstly of forecasting energy production using the forecasting agents and calculating the equivalent emitted CO2. Secondly, a dedicated agent calculates the total CO2 emitted from all the available sources. It then computes the benefits of using renewable energy sources as an alternative way to meet the electric load in terms of emission mitigation and economizing natural gas consumption. The forecasting models showed satisfying results, and the simulation scenario showed that using renewable energy can help reduce the emissions by 369 tons of CO2 (3%) per day.
{"title":"A collaborative predictive multi-agent system for forecasting carbon emissions related to energy consumption","authors":"S. Bouziane, Tarek Khadir, J. Dugdale","doi":"10.3233/MGS-210342","DOIUrl":"https://doi.org/10.3233/MGS-210342","url":null,"abstract":"Energy production and consumption are one of the largest sources of greenhouse gases (GHG), along with industry, and is one of the highest causes of global warming. Forecasting the environmental cost of energy production is necessary for better decision making and easing the switch to cleaner energy systems in order to reduce air pollution. This paper describes a hybrid approach based on Artificial Neural Networks (ANN) and an agent-based architecture for forecasting carbon dioxide (CO2) issued from different energy sources in the city of Annaba using real data. The system consists of multiple autonomous agents, divided into two types: firstly, forecasting agents, which forecast the production of a particular type of energy using the ANN models; secondly, core agents that perform other essential functionalities such as calculating the equivalent CO2 emissions and controlling the simulation. The development is based on Algerian gas and electricity data provided by the national energy company. The simulation consists firstly of forecasting energy production using the forecasting agents and calculating the equivalent emitted CO2. Secondly, a dedicated agent calculates the total CO2 emitted from all the available sources. It then computes the benefits of using renewable energy sources as an alternative way to meet the electric load in terms of emission mitigation and economizing natural gas consumption. The forecasting models showed satisfying results, and the simulation scenario showed that using renewable energy can help reduce the emissions by 369 tons of CO2 (3%) per day.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"13 1","pages":"39-58"},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84976237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Telework is an important alternative to work that seeks to enhance employees’ safety and well-being while reducing the company costs. Employees can work anytime, any where and under high mobility conditions using new devices. Therefore, the access control of remote exchanges of Enterprise Content Management systems (ECM) have to take into consideration the diversity of users’ devices and context conditions in a telework open network. Different access control models were proposed in the literature to deal with the dynamic nature of users’ context and devices. However, most access control models rely on a centralized management of permissions by an authorization entity which can reduce its performance with the increase of number of users and requests in an open network. Moreover, they often depend on the administrator’s intervention to add new devices’ authorization and to set permissions on resources. In this paper, we suggest a distributed management of access control for telework open networks that focuses on an agent-based access control framework. The framework uses a multi-level rule engine to dynamically generate policies. We conducted a usability test and an experiment to evaluate the security performance of the proposed framework. The result of the experiment shows that the ability to resist deny of service attacks over time increased in the proposed distributed access control management compared with the centralized approach.
{"title":"Agent-based access control framework for enterprise content management","authors":"Nadia Hocine","doi":"10.3233/mgs-210346","DOIUrl":"https://doi.org/10.3233/mgs-210346","url":null,"abstract":"Telework is an important alternative to work that seeks to enhance employees’ safety and well-being while reducing the company costs. Employees can work anytime, any where and under high mobility conditions using new devices. Therefore, the access control of remote exchanges of Enterprise Content Management systems (ECM) have to take into consideration the diversity of users’ devices and context conditions in a telework open network. Different access control models were proposed in the literature to deal with the dynamic nature of users’ context and devices. However, most access control models rely on a centralized management of permissions by an authorization entity which can reduce its performance with the increase of number of users and requests in an open network. Moreover, they often depend on the administrator’s intervention to add new devices’ authorization and to set permissions on resources. In this paper, we suggest a distributed management of access control for telework open networks that focuses on an agent-based access control framework. The framework uses a multi-level rule engine to dynamically generate policies. We conducted a usability test and an experiment to evaluate the security performance of the proposed framework. The result of the experiment shows that the ability to resist deny of service attacks over time increased in the proposed distributed access control management compared with the centralized approach.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"155 1","pages":"129-143"},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79808990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Rwegasira, I. Dhaou, M. Ebrahimi, Anders Hallén, N. Mvungi, H. Tenhunen
The energy sector is experiencing a revolution that is fuelled by a multitude of factors. Among them are the aging grid system, the need for cleaner energy and the increasing demands on energy sector. The demand-response program is an advanced feature in smart grid that strives to match suppliers to their demands using price-based and incentive programs. The objective of the work is to analyse the performance of the load shedding technique using dynamic pricing algorithm. The system was designed using multi-agent system (MAS) for a DC microgrid capable of real-time monitoring and controlling of power using price-based demand-response program. As a proof of concept, the system was implemented using intelligent physical agents, Java Agent Development Framework (JADE), and agent simulation platform (REPAST) with two residential houses (non-critical loads) and one hospital (critical load). The architecture has been implemented using embedded devices, relays, and sensors to control the operations of load shedding and energy trading in residential areas that have no access to electricity. The measured results show that the system can shed the load with the latency of less than 600 ms, and energy cost saving with an individual houses by 80% of the total cost with 2USD per day. The outcome of the studies demonstrates the effectiveness of the proposed multi-agent approach for real-time operation of a microgrid and the implementation of demand-response program.
{"title":"Energy trading and control of islanded DC microgrid using multi-agent systems","authors":"D. Rwegasira, I. Dhaou, M. Ebrahimi, Anders Hallén, N. Mvungi, H. Tenhunen","doi":"10.3233/mgs-210345","DOIUrl":"https://doi.org/10.3233/mgs-210345","url":null,"abstract":"The energy sector is experiencing a revolution that is fuelled by a multitude of factors. Among them are the aging grid system, the need for cleaner energy and the increasing demands on energy sector. The demand-response program is an advanced feature in smart grid that strives to match suppliers to their demands using price-based and incentive programs. The objective of the work is to analyse the performance of the load shedding technique using dynamic pricing algorithm. The system was designed using multi-agent system (MAS) for a DC microgrid capable of real-time monitoring and controlling of power using price-based demand-response program. As a proof of concept, the system was implemented using intelligent physical agents, Java Agent Development Framework (JADE), and agent simulation platform (REPAST) with two residential houses (non-critical loads) and one hospital (critical load). The architecture has been implemented using embedded devices, relays, and sensors to control the operations of load shedding and energy trading in residential areas that have no access to electricity. The measured results show that the system can shed the load with the latency of less than 600 ms, and energy cost saving with an individual houses by 80% of the total cost with 2USD per day. The outcome of the studies demonstrates the effectiveness of the proposed multi-agent approach for real-time operation of a microgrid and the implementation of demand-response program.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"1 1","pages":"113-128"},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77574032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Human fall detection is a subcategory of ambient assisted living. Falls are dangerous for old aged people especially those who are unaccompanied. Detection of falls as early as possible along with high accuracy is indispensable to save the person otherwise it may lead to physical disability even death also. The proposed fall detection system is implemented in the edge computing scenario. An adaptive window-based approach is proposed here for feature extraction because window size affects the performance of the classifier. For training and testing purposes two public datasets and our collected dataset have been used. Anomaly identification based on a support vector machine with an enhanced chi-square kernel is used here for the classification of Activities of Daily Living (ADL) and fall activities. Using the proposed approach 100% sensitivity and 98.08% specificity have been achieved which are better when compared with three recent research based on unsupervised learning. One of the important aspects of this study is that it is also validated on actual real fall data and got 100% accuracy. This complete fall detection model is implemented in the fog computing scenario. The proposed approach of adaptive window based feature extraction is better than static window based approaches and three recent fall detection methods.
{"title":"Adaptive window based fall detection using anomaly identification in fog computing scenario","authors":"Rashmi Shrivastava, Manju Pandey","doi":"10.3233/MGS-210341","DOIUrl":"https://doi.org/10.3233/MGS-210341","url":null,"abstract":"Human fall detection is a subcategory of ambient assisted living. Falls are dangerous for old aged people especially those who are unaccompanied. Detection of falls as early as possible along with high accuracy is indispensable to save the person otherwise it may lead to physical disability even death also. The proposed fall detection system is implemented in the edge computing scenario. An adaptive window-based approach is proposed here for feature extraction because window size affects the performance of the classifier. For training and testing purposes two public datasets and our collected dataset have been used. Anomaly identification based on a support vector machine with an enhanced chi-square kernel is used here for the classification of Activities of Daily Living (ADL) and fall activities. Using the proposed approach 100% sensitivity and 98.08% specificity have been achieved which are better when compared with three recent research based on unsupervised learning. One of the important aspects of this study is that it is also validated on actual real fall data and got 100% accuracy. This complete fall detection model is implemented in the fog computing scenario. The proposed approach of adaptive window based feature extraction is better than static window based approaches and three recent fall detection methods.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"284 1","pages":"15-37"},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77048153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Qawasmeh, Salah Taamneh, A. Aljammal, Nabhan Hamadneh, Mustafa Banikhalaf, M. Kharabsheh
Different high performance techniques, such as profiling, tracing, and instrumentation, have been used to tune and enhance the performance of parallel applications. However, these techniques do not show how to explore the potential of parallelism in a given application. Animating and visualizing the execution process of a sequential algorithm provide a thorough understanding of its usage and functionality. In this work, an interactive web-based educational animation tool was developed to assist users in analyzing sequential algorithms to detect parallel regions regardless of the used parallel programming model. The tool simplifies algorithms’ learning, and helps students to analyze programs efficiently. Our statistical t-test study on a sample of students showed a significant improvement in their perception of the mechanism and parallelism of applications and an increase in their willingness to learn algorithms and parallel programming.
{"title":"Parallelism exploration in sequential algorithms via animation tool","authors":"A. Qawasmeh, Salah Taamneh, A. Aljammal, Nabhan Hamadneh, Mustafa Banikhalaf, M. Kharabsheh","doi":"10.3233/mgs-210347","DOIUrl":"https://doi.org/10.3233/mgs-210347","url":null,"abstract":"Different high performance techniques, such as profiling, tracing, and instrumentation, have been used to tune and enhance the performance of parallel applications. However, these techniques do not show how to explore the potential of parallelism in a given application. Animating and visualizing the execution process of a sequential algorithm provide a thorough understanding of its usage and functionality. In this work, an interactive web-based educational animation tool was developed to assist users in analyzing sequential algorithms to detect parallel regions regardless of the used parallel programming model. The tool simplifies algorithms’ learning, and helps students to analyze programs efficiently. Our statistical t-test study on a sample of students showed a significant improvement in their perception of the mechanism and parallelism of applications and an increase in their willingness to learn algorithms and parallel programming.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"17 1","pages":"145-158"},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78532983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the rapid development of data and IT technology, cloud computing is gaining more and more attention, and many users are attracted to this paradigm because of the reduction in cost and the dynamic allocation of resources. Load balancing is one of the main challenges in cloud computing system. It redistributes workloads across computing nodes within cloud to minimize computation time, and to improve the use of resources. This paper proposes an enhanced ‘Active VM load balancing algorithm’ based on fuzzy logic and k-means clustering to reduce the data center transfer cost, the total virtual machine cost, the data center processing time and the response time. The proposed method is realized using Java and CloudAnalyst Simulator. Besides, we have compared the proposed algorithm with other task scheduling approaches such as Round Robin algorithm, Throttled algorithm, Equally Spread Current Execution Load algorithm, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). As a result, the proposed algorithm performs better in terms of service rate and response time.
{"title":"Enhanced active VM load balancing algorithm using fuzzy logic and K-means clustering","authors":"Mostefa Hamdani, Youcef Aklouf","doi":"10.3233/MGS-210343","DOIUrl":"https://doi.org/10.3233/MGS-210343","url":null,"abstract":"With the rapid development of data and IT technology, cloud computing is gaining more and more attention, and many users are attracted to this paradigm because of the reduction in cost and the dynamic allocation of resources. Load balancing is one of the main challenges in cloud computing system. It redistributes workloads across computing nodes within cloud to minimize computation time, and to improve the use of resources. This paper proposes an enhanced ‘Active VM load balancing algorithm’ based on fuzzy logic and k-means clustering to reduce the data center transfer cost, the total virtual machine cost, the data center processing time and the response time. The proposed method is realized using Java and CloudAnalyst Simulator. Besides, we have compared the proposed algorithm with other task scheduling approaches such as Round Robin algorithm, Throttled algorithm, Equally Spread Current Execution Load algorithm, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). As a result, the proposed algorithm performs better in terms of service rate and response time.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"56 1","pages":"59-82"},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84509466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Data-intensive cloud computing systems are growing year by year due to the increasing volume of data. In this context, data replication technique is frequently used to ensure a Quality of service, e.g., performance. However, most of the existing data replication strategies just reproduce the same number of replicas on some nodes, which is certainly not enough for more accurate results. To solve these problems, we propose a new data Replication and Placement strategy based on popularity of User Requests Group (RPURG). It aims to reduce the tenant response time and maximize benefit for the cloud provider while satisfying the Service Level Agreement (SLA). We demonstrate the validity of our strategy in a performance evaluation study. The result of experimentation shown robustness of RPURG.
{"title":"A new popularity-based data replication strategy in cloud systems","authors":"Abdenour Lazeb, R. Mokadem, Ghalem Belalem","doi":"10.3233/mgs-210348","DOIUrl":"https://doi.org/10.3233/mgs-210348","url":null,"abstract":"Data-intensive cloud computing systems are growing year by year due to the increasing volume of data. In this context, data replication technique is frequently used to ensure a Quality of service, e.g., performance. However, most of the existing data replication strategies just reproduce the same number of replicas on some nodes, which is certainly not enough for more accurate results. To solve these problems, we propose a new data Replication and Placement strategy based on popularity of User Requests Group (RPURG). It aims to reduce the tenant response time and maximize benefit for the cloud provider while satisfying the Service Level Agreement (SLA). We demonstrate the validity of our strategy in a performance evaluation study. The result of experimentation shown robustness of RPURG.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"56 1","pages":"159-177"},"PeriodicalIF":0.7,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88782019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Privacy preserved outsourced data access control is a hard task under the control of thirdâparty storage server. To overcome obstacles in the third party based scenario, Attribute-based signcryption system with bilinear pairing tool is one of the most suitable methods in cloud. It maintains the basic features of security like, authenticity, confidentiality, public verifiability, owner privacy, etc. Although, this method has some challenges like a centralized authority used for user secret key generation for de-signcryption operation, and lack in competent attribute revocation. To overcome the issues, we have proposed a scheme of attribute revocable privacy preserved outsourced based data access control mechanism using Attribute-based signcryption. The proposed method allows multi-authorities for assigning both attribute and secret keys for users along with trusted certified authority, which provides security parameters. The analysis of the proposed method shows less computation cost in decryption and authentication verification. The almost same performance and efficiency is found while comparing with the existing schemes after adding new features.
{"title":"Privacy preserved secured outsourced cloud data access control scheme with efficient multi-authority attribute based signcryption","authors":"Somen Debnath, B. Bhuyan, A. Saha","doi":"10.3233/mgs-200338","DOIUrl":"https://doi.org/10.3233/mgs-200338","url":null,"abstract":"Privacy preserved outsourced data access control is a hard task under the control of thirdâparty storage server. To overcome obstacles in the third party based scenario, Attribute-based signcryption system with bilinear pairing tool is one of the most suitable methods in cloud. It maintains the basic features of security like, authenticity, confidentiality, public verifiability, owner privacy, etc. Although, this method has some challenges like a centralized authority used for user secret key generation for de-signcryption operation, and lack in competent attribute revocation. To overcome the issues, we have proposed a scheme of attribute revocable privacy preserved outsourced based data access control mechanism using Attribute-based signcryption. The proposed method allows multi-authorities for assigning both attribute and secret keys for users along with trusted certified authority, which provides security parameters. The analysis of the proposed method shows less computation cost in decryption and authentication verification. The almost same performance and efficiency is found while comparing with the existing schemes after adding new features.","PeriodicalId":43659,"journal":{"name":"Multiagent and Grid Systems","volume":"93 1","pages":"409-432"},"PeriodicalIF":0.7,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85652213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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