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A classification-based privacy-preserving decision-making for secure data sharing in Internet of Things assisted applications

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Digital Communications and Networks 2022年第4期8卷 436-445页

作者： Alaa Omran Almagrabi A.K.Bashir Department of Information Systems Faculty of Computing and Information Technology(FCIT)King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK

The introduction of the Internet of Things(IoT)paradigm serves as pervasive resource access and sharing platform for different real-time *** resource availability,access,and allocation provide a better quality of user experience regardless of the application type and ***,privacy remains an open issue in this ubiquitous sharing platform due to massive and replicated data *** this paper,privacy-preserving decision-making for the data-sharing scheme is *** scheme is responsible for improving the security in data sharing without the impact of replicated resources on communicating *** this scheme,classification learning is used for identifying replicas and accessing granted resources *** on the trust score of the available resources,this classification is recurrently performed to improve the reliability of information *** user-level decisions for information sharing and access are made using the classification of the resources at the time of *** proposed scheme is verified using the metrics access delay,success ratio,computation complexity,and sharing loss.

关键词： Classification learning Data mining IoT Privacy-preserving Resource replication

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Predicting Energy Consumption Using Stacked LSTM Snapshot Ensemble

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Big Data Mining and Analytics 2024年第2期7卷 247-270页

作者： Mona Ahamd Alghamdi Abdullah S.A.L-Malaise AL-Ghamdi Mahmoud Ragab Information Systems Department Faculty of Computing and Information Technology(FCIT)King Abdulaziz University(KAU)Jeddah 21589Kingdom of Saudi Arabia Information Systems Department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with School of EngineeringComputing and DesignDar Al-Hekma UniversityJeddah 22246Kingdom of Saudi Arabia Information Technology Department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with Mathematics DepartmentFaculty of ScienceAl-Azhar UniversityNaser City 11884Egypt

The ability to make accurate energy predictions while considering all related energy factors allows production plants,regulatory bodies,and governments to meet energy demand and assess the effects of energy-saving *** energy consumption falls within normal parameters,it will be possible to use the developed model to predict energy consumption and develop improvements and mitigating measures for energy *** objective of this model is to accurately predict energy consumption without data limitations and provide results that are easily *** proposed model is an implementation of the stacked Long Short-Term Memory(LSTM)snapshot ensemble combined with the Fast Fourier Transform(FFT)and *** and Berard’s Individual Household Electric-Power Consumption(IHEPC)dataset incorporated with weather data are used to analyse the model’s accuracy with predicting energy *** model is trained,and the results measured using Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and coefficient of determination(R^(2))metrics are 0.020,0.013,0.017,and 0.999,*** stacked LSTM snapshot ensemble performs better than the compared models based on prediction accuracy and minimized *** results of this study show that prediction accuracy is high,and the model’s stability is high as *** model shows that high levels of accuracy prove accurate predictive ability,and together with high levels of stability,the model has good interpretability,which is not typically accounted for in ***,this study shows that it can be inferred.

关键词： energy consumption prediction Artificial Intelligence(AI) Deep Learning(DL) snapshot ensemble

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Service-Aware Access Control Procedure for Blockchain Assisted Real-Time Applications

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Computers, Materials & Continua 2021年第6期67卷 3649-3667页

作者： Alaa Omran Almagrabi A.K.Bashir Department of Information Systems Faculty of Computing and Information Technology(FCIT)King Abdul Aziz University(KAU)JeddahKingdom of Saudi Arabia School of Information and Communication Engineering University of Electronic Science and Technology of China(UESTC)ChengduChina

The design of distributed ledger,Asymmetric Key Algorithm(AKA)blockchain systems,is prominent in administering security and access control in various real-time services and *** assimilation of blockchain systems leverages the reliable access and secure service provisioning of the ***,the distributed ledger technology’s access control and chained decisions are defaced by pervasive and service *** results in degrading security through unattended access control for limited-service *** this article,a service-aware access control procedure(SACP)is introduced to address the afore-mentioned *** proposed SACP denes attended access control for all the service session by identifying the users and service provider *** distributed nature of the ledger systems and classication tree learning are combined to determine unattended *** sole access is determined by summarizing the closed and open access requests and the service provider’s availability and integrity *** this process,the learning process classies the secured access request and completed the integrity checks of the current and previous service *** classication-based access administration reduces the service disconnections and false access rate of the applications.

关键词： Access control blockchain classication trees service dissemination unattended access

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Density Grid-based Clustering for Wireless Sensors Networks

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Procedia Computer Science 2015年 65卷 35-47页

作者： Manal Abdullah Hend Nour Eldin Tahani Al-Moshadak Rawan Alshaik Inas Al-Anesi Faculty of Computing and Information Technology FCIT King Abdulaziz University KAU Jeddah SA

Wireless Sensor Networks WSNs are special networks consist of devices (sensor nodes) in large numbers and spatial distribution. They have various sensing capability and cooperate to accomplish common task. Clustering is one of the most effective techniques used to solve the problem of energy consumption in WSNs. Grid based clustering has proven its efficiency specially for high dynamic networks. The girds’ strategy used in this research is implemented on dense network and divides the network area into multiple grid cells with different densities (High, Low, and empty). Then grids are combined to form clusters as normal and advanced clusters. Cluster head is elected for each cluster based on high energy. This new suggested strategy is implemented and tested using MATLAB. The results show that this suggested strategy works well at 150 node WSN and grid size between 5-10 units where the network life time is 633 seconds approximately.

关键词： Grid-Based Clustering Density-based Clustering Clustering Algorithms Wireless Sensor Network Cluster head Election

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Medium Access Control Protocols for Wireless Sensor Networks Classifications and Cross-Layering

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Procedia Computer Science 2015年 65卷 4-16页

作者： Ahlam Saud Althobaiti Manal Abdullah College of Computing and Information Technology Taif Univerfity KSA Faculty of Computing and Information Technology FCIT King Abdulaziz University KAU Jeddah KSA

Wireless Sensor Networks (WSNs) have become a leading solution in many important applications such as intrusion detection, target tracking, industrial automation, smart building and so on. The sensor nodes are generally unattended after their deployment in hazardous, hostile or remote areas. These nodes have to work with their limited and non replenish able energy resources. Energy efficiency is one of the main design objectives for these sensor networks. Medium Access Control MAC sub-layer is part of Data Link layer in WSN's protocol stack. The energy consumption of sensor nodes is greatly affected by MAC protocol which controls the node radio functionalities. In this paper, the design requirements of energy efficient MAC protocols for WSNs are reviewed and classified. Several MAC protocols for the WSNs are described emphasizing their strength and weakness. Also, the paper introduces cross-layer protocols as a concept that leads to benefit from the network resources as well as prolonging network lifetime. The paper is appended by comparison between existing protocols regarding protocol's type, cross-layer support, and MAC scheduling. Finally, future research directions in the MAC protocol design are proposed.

关键词： Medium Access Control (MAC) Protocols Wireless Sensor Networks (WSN) Cross-Layering

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Energy efficient optimized routing algorithm (EEORA)

Energy efficient optimized routing algorithm (EEORA)

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International Conference on Communication, Management and information technology, ICCMIT 2016

作者： Alharbe, N. Abdullah, M. College of Computer Science and Engineering Taibah University Al Madinah al Munawwarah Saudi Arabia Faculty of Computing and Information Technology FCIT King Abdulaziz University KAU Jeddah Saudi Arabia

ISBN: (纸本)9781315375083

As a part from the great revolution that was occurred recently, a continuous improvement was and still achieved in communication and network field. Wireless Sensor Networks was emerged as a result for this development, extensive researches were introduced in order to improve it is performance since it is now employed within several tactical applications, including;detection and monitoring applications. Routing process is considered one of the hottest research areas throughout the last years, several routing protocols were proposed in order to improve the performance of the network. In this paper, a new Energy Efficient Optimized Routing Algorithm (EEORA) is proposed and implemented by hybridization for the features of flat and Hierarchal routing techniques. EEORA routing process is performed into two stages, clustering and data communication phases. MATLAB program was employed in simulating the model of the proposed routing protocol for both Wireless Sensor Networks (WSNs) and Dense Wireless Sensor Networks (DWSNs). The results showed that more scalability is obtained by EEORA over other considered routing protocols. The results also showed that improved performance in terms of, energy consumption, end-to-end delay, network life time and throughput is also achieved by EEORA. © 2017 Taylor & Francis Group, London.

关键词： Routing algorithms

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Cross-layer quality of service protocols for wireless multimedia sensor networks

Cross-layer quality of service protocols for wireless multim...

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International Conference on Communication, Management and information technology, ICCMIT 2016

作者： AlAmri, Ablah Abdullah, Manal Jeddah Community College JCC King Abdulaziz University KAU Jeddah Saudi Arabia Faculty of Computing and Information Technology FCIT King Abdulaziz University KAU Jeddah Saudi Arabia

ISBN: (纸本)9781315375083

Wireless Multimedia Sensor Networks (WMSNs) recently gained attention of many researchers, WMSNs have sensor nodes that are deployed to extract information from surrounding environment, processing information locally then transmit it to sink/base station wirelessly. Multimedia data include audio, image, and video. Sensor nodes are limited in battery, memory and CPU capability. Multimedia data is larger in volume than scalar data, thus transmitting multimedia data require stick constraint on quality of services in term of energy, throughput and end to end delay. Cross layer architecture is a new concept which combine several layers to allow integration and exchange information among them more efficiently than classical layered approach. This paper discusses and compares between existing cross layer protocols for WMSNs which cross functionalities of adjacent or non-adjacent layers. © 2017 Taylor & Francis Group, London.

关键词： Sensor nodes

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A Survey on the Role of Complex Networks in IoT and Brain Communication

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Computers, Materials & Continua 2023年第9期76卷 2573-2595页

作者： Vijey Thayananthan Aiiad Albeshri Hassan A.Alamri Muhammad Bilal Qureshi Muhammad Shuaib Qureshi Cybersecurity Department Faculty of ComputingEngineering and ScienceUniversity of SouthWalesWalesUK Department of Computer Science Faculty of Computing and Information Technology(FCIT)King Abdulaziz UniversityJeddah21589Saudi Arabia Computer Science Department Umm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science&IT University of Lakki MarwatLakki Marwat28420KPKPakistan Department of Computer Engineering Chungnam National UniversityDaejeon34134Republic of Korea

Complex networks on the Internet of Things(IoT)and brain communication are the main focus of this *** benefits of complex networks may be applicable in the future research directions of 6G,photonic,IoT,brain,etc.,communication *** data traffic,huge capacity,minimal level of dynamic latency,*** some of the future requirements in 5G+and 6G communication *** emerging communication,technologies such as 5G+/6G-based photonic sensor communication and complex networks play an important role in improving future requirements of IoT and brain *** this paper,the state of the complex system considered as a complex network(the connection between the brain cells,neurons,etc.)needs measurement for analyzing the functions of the neurons during brain ***,we measure the state of the complex system through *** 5G+/6G-based photonic sensor nodes,finding observability influenced by the concept of contraction provides the stability of *** IoT or any sensors fail to measure the state of the connectivity in the 5G+or 6G communication due to external noise and attacks,some information about the sensor nodes during the communication will be ***,neurons considered sing the complex networks concept neuron sensors in the brain lose communication and ***,affected sensor nodes in a contraction are equivalent to compensate for maintaining stability *** this compensation,loss of observability depends on the contraction size which is a key factor for employing a complex *** analyze the observability recovery,we can use a contraction detection algorithm with complex network *** survey paper shows that contraction size will allow us to improve the performance of brain communication,stability of neurons,etc.,through the clustering coefficient considered in the contraction detection *** addition,we discuss the scalability of IoT communication using 5G+/6G

关键词： Complex networks emerging communication IoT based on 6G systems neuroscience photonic technology

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Smart Infrastructure and Applications 1

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丛书名： EAI/Springer Innovations in Communication and computing

1000年

作者： Rashid Mehmood Simon See Iyad Katib Imrich Chlamtac

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Analysis of Eight Data Mining Algorithms for Smarter Internet of Things (IoT)

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Procedia Computer Science 2016年 98卷 437-442页

作者： Furqan Alam Rashid Mehmood Iyad Katib Aiiad Albeshri Department of Computer Science Faculty of Computing and Information Technology (FCIT) King Abdulaziz University Jeddah KSA High Performance Computing Center King Abdulaziz University Jeddah KSA

Internet of Things (IoT) is set to revolutionize all aspects of our lives. The number of objects connected to IoT is expected to reach 50 billion by 2020, giving rise to an enormous amounts of valuable data. The data collected from the IoT devices will be used to understand and control complex environments around us, enabling better decision making, greater automation, higher efficiencies, productivity, accuracy, and wealth generation. Data mining and other artificial intelligence methods would play a critical role in creating smarter IoTs, albeit with many challenges. In this paper, we examine the applicability of eight well-known data mining algorithms for IoT data. These include, among others, the deep learning artificial neural networks (DLANNs), which build a feed forward multi-layer artificial neural network (ANN) for modelling high-level data abstractions. Our preliminary results on three real IoT datasets show that C4.5 and C5.0 have better accuracy, are memory efficient and have relatively higher processing speeds. ANNs and DLANNs can provide highly accurate results but are computationally expensive.

关键词： Internet of Things (IoT) Support Vector Machine (SVM) K-Nearest Neighbours (KNN) Linear Discriminant Analysis (LDA) Naïve Bayes (NB) C4.5 C5.0 Artificial Neural Networks (ANNs) Deep Learning ANNs (DLANNs) Big Data Smart Cities

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