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All Journal International Journal of Electrical and Computer Engineering
Mohammed Al-Shabi
Taibah University
Computer Science & IT Electrical & Electronics Engineering

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Using deep learning to detecting abnormal behavior in internet of things Mohammed Al-Shabi; Anmar Abuhamdah
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 2: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i2.pp2108-2120

Abstract

The development of the internet of things (IoT) has increased exponentially, creating a rapid pace of changes and enabling it to become more and more embedded in daily life. This is often achieved through integration: IoT is being integrated into billions of intelligent objects, commonly labeled “things,” from which the service collects various forms of data regarding both these “things” themselves as well as their environment. While IoT and IoT-powered decices can provide invaluable services in various fields, unauthorized access and inadvertent modification are potential issues of tremendous concern. In this paper, we present a process for resolving such IoT issues using adapted long short-term memory (LSTM) recurrent neural networks (RNN). With this method, we utilize specialized deep learning (DL) methods to detect abnormal and/or suspect behavior in IoT systems. LSTM RNNs are adopted in order to construct a high-accuracy model capable of detecting suspicious behavior based on a dataset of IoT sensors readings. The model is evaluated using the Intel Labs dataset as a test domain, performing four different tests, and using three criteria: F1, Accuracy, and time. The results obtained here demonstrate that the LSTM RNN model we create is capable of detecting abnormal behavior in IoT systems with high accuracy.
Improving blockchain security for the internet of things: challenges and solutions Mohammed Al-Shabi; Abdulrahman Al-Qarafi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5619-5629

Abstract

Due to its uniquely suited to the knowledge era, the blockchain technology has currently become highly appealing to the next generation. In addition, such technology has been recently extended to the internet of things (IoT). In essence, the blockchain concept necessitates the use of a decentralized data operation system to store as well as to distribute data and the transactions across the net. Therefore, this study examines the specific concept of the blockchain as a decentralized data management system in the face of probable protection threats. Furthermore, it discusses the present solutions that can be used to counteract those attacks. The blockchain security enhancement solutions are included in this study by summarizing the key points of these solutions. Several blockchain systems and safety devices that register security defenselessness can be developed using such key points. At last, this paper discusses the pending matters and the outlook research paths of blockchain-IoT systems.
Co-Authors Abdulrahman Al-Qarafi Anmar Abuhamdah