M
Muder Almiani
Researcher at Al-Hussein Bin Talal University
Publications - 50
Citations - 538
Muder Almiani is an academic researcher from Al-Hussein Bin Talal University. The author has contributed to research in topics: Cloud computing & Computer science. The author has an hindex of 7, co-authored 43 publications receiving 225 citations. Previous affiliations of Muder Almiani include Gulf University for Science and Technology & University of Bridgeport.
Papers
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Journal ArticleDOI
Deep recurrent neural network for IoT intrusion detection system
TL;DR: An artificially full-automated intrusion detection system for Fog security against cyber-attacks using multi-layered of recurrent neural networks designed to be implemented for Fog computing security that is very close to the end-users and IoT devices is presented.
Journal ArticleDOI
Scalable and Secure Big Data IoT System Based on Multifactor Authentication and Lightweight Cryptography
Saleh Atiewi,Amer Al-Rahayfeh,Muder Almiani,Salman Yussof,Omar Alfandi,Ahed Abugabah,Yaser Jararweh +6 more
TL;DR: The proposed cloud–IoT architecture supported by multifactor authentication and lightweight cryptography encryption schemes to protect big data system is implemented and evaluated using metrics such as computational time, security strength, encryption time, and decryption time.
Journal ArticleDOI
Novel Approach to Task Scheduling and Load Balancing Using the Dominant Sequence Clustering and Mean Shift Clustering Algorithms
TL;DR: This work proposes a novel approach that uses dominant sequence clustering (DSC) for task scheduling and a weighted least connection (WLC) algorithm for load balancing and evaluates the proposed architecture using metrics such as response time, makespan, resource utilization, and service reliability.
Proceedings ArticleDOI
Intelligent intrusion detection system using clustered self organized map
TL;DR: An intelligent intrusion detection system using clustered version of Self-Organized Map (SOM) network is built using hierarchical agglomerative clustering using k-means to address the issues of sensitivity and time consumption for each connection record processing.
Journal ArticleDOI
State-of-art review of information diffusion models and their impact on social network vulnerabilities
TL;DR: A comparative study on the existing models of information diffusion on the Internet such as the Ising model, Sznajd model, SIRmodel, SICR model, Game theory and social networking services models is provided.