Browsing KINDI Center for Computing Research by Title
Now showing items 22-41 of 272
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Advanced Deep Learning for Resource Allocation and Security Aware Data Offloading in Industrial Mobile Edge Computing
( Mary Ann Liebert Inc. , 2021 , Article)The Internet of Things (IoT) is permeating our daily lives through continuous environmental monitoring and data collection. The promise of low latency communication, enhanced security, and efficient bandwidth utilization ... -
Advanced Ensemble Deep Random Vector Functional Link for Eye-Tracking-based Situation Awareness Recognition
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Conference)Situation awareness (SA) plays a significant role in takeover transitions from autonomous to manual driving. Previous researchers have shown that eye movement signals can be used for SA recognition. Moreover, ensemble deep ... -
AI-powered malware detection with Differential Privacy for zero trust security in Internet of Things networks
( Elsevier , 2024 , Article)The widespread usage of Android-powered devices in the Internet of Things (IoT) makes them susceptible to evolving cybersecurity threats. Most healthcare devices in IoT networks, such as smart watches, smart thermometers, ... -
Almost BPXOR Coding Technique for Tolerating Three Disk Failures in RAID7 Architectures
( Hamad bin Khalifa University Press (HBKU Press) , 2018 , Conference)Redundant Array of Independent Disks (RAID) storage architectures provide protection of digital infrastructure against potential disks failures. For example, RAID-5 and RAID-6 architectures provide protection against one ... -
Alzheimer’s disease diagnosis from MRI and SWI fused image using self adaptive differential evolutionary RVFL classifier
( Elsevier , 2025 , Article)Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that involves gradual memory loss and eventually leads to severe cognitive decline at the final stage. Advanced neuroimaging modalities, including magnetic ... -
An efficient instance hiding scheme
( Association for Computing Machinery , 2016 , Conference)Delegating computation, which is applicable to many practical contexts such as cloud computing or pay-TV system, concerns the task where a computationally weak client wants to securely compute a very complex function f on ... -
An enhanced ensemble deep random vector functional link network for driver fatigue recognition
( Elsevier , 2023 , Article)This work investigated the use of an ensemble deep random vector functional link (edRVFL) network for electroencephalogram (EEG)-based driver fatigue recognition. Against the low feature learning capability of the edRVFL ... -
An evolutionary multiobjective method based on dominance and decomposition for feature selection in classification
( Science China Press , 2024 , Article)Feature selection in classification can be considered a multiobjective problem with the objectives of increasing classification accuracy and decreasing the size of the selected feature subset. Dominance-based and ... -
An Interactive Visualization Web Solution for Electricity Consumption in Qatar
( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference)The amount of raw data related to electricity companies is increasing rapidly with the increase of construction sites, population and Qatar preparation for 2022 world cup. A question arises from this situation is: How can ... -
Analysis of Predictive Models for Revealing Household Characteristics using Smart Grid Data
( IEEE Computer Society , 2023 , Conference)The Smart Grid Advanced Metering Infrastructure (AMI) has revolutionized the smart grid network, generating vast amounts of data that can be utilized for diverse objectives, one of which is Household Characteristics ... -
Android Malware Detection and Classification using Stacked Machine Learning
( Institute of Electrical and Electronics Engineers Inc. , 2023 , Conference)The widespread use of Android smartphones in daily life can be attributed to the extensive prevalence stemming from the Android OS and the availability of open-source applications. People have become accustomed to performing ... -
Anonymizing transactional datasets
( IOS Press , 2015 , Article)In this paper, we study the privacy breach caused by unsafe correlations in transactional data where individuals have multiple tuples in a dataset. We provide two safety constraints to guarantee safe correlation of the ... -
Applying zero trust security principles to defence mechanisms against data exfiltration attacks
( wiley , 2021 , Book chapter)The zero-trust principle explicitly verifies that the authentication and authorization of all actions are performed regardless of the requesting user's credentials or permissions. This chapter presents the details of a ... -
An archive-assisted multi-modal multi-objective evolutionary algorithm
( Elsevier , 2024 , Article)The multi-modal multi-objective optimization problems (MMOPs) pertain to characteristic of the decision space that exhibit multiple sets of Pareto optimal solutions that are either identical or similar. The resolution of ... -
Assessing the Effect of Model Poisoning Attacks on Federated Learning in Android Malware Detection
( Association for Computing Machinery , 2024 , Conference)Android devices are central to our daily lives, which leads to an increase in mobile security threats. Attackers try to exploit vulnerabilities and steal personal information from the installed applications on these devices. ... -
Assessing the effects of data selection and representation on the development of reliable E. coli sigma 70 promoter region predictors
( Public Library of Science , 2015 , Article)As the number of sequenced bacterial genomes increases, the need for rapid and reliable tools for the annotation of functional elements (e.g., transcriptional regulatory elements) becomes more desirable. Promoters are the ... -
Automated layer-wise solution for ensemble deep randomized feed-forward neural network
( Elsevier B.V. , 2022 , Article)The randomized feed-forward neural network is a single hidden layer feed-forward neural network that enables efficient learning by optimizing only the output weights. The ensemble deep learning framework significantly ... -
Automatic generation of optimized workflow for distributed computations on large-scale matrices
( Springer Verlag , 2014 , Conference)Efficient evaluation of distributed computation on large-scale data is prominent in modern scientific computation; especially analysis of big data, image processing and data mining applications. This problem is particularly ... -
Automatic variable reduction
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)A variable reduction strategy (VRS) is an effective method to accelerate the optimization process of evolutionary algorithms (EAs) by simplifying the corresponding optimization problems. Unfortunately, the VRS is manually ... -
Battery-Induced Load Hiding and Its Utility Consequences
( Institute of Electrical and Electronics Engineers Inc. , 2024 , Conference)The introduction of smart grids allows utility providers to collect detailed data about consumers, which can be utilized to enhance grid efficiency and reliability. However, this data collection also raises privacy concerns. ...
