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Adel R. Alharbi

Researcher at Information Technology University

Publications -  39
Citations -  181

Adel R. Alharbi is an academic researcher from Information Technology University. The author has contributed to research in topics: Computer science & Encryption. The author has an hindex of 4, co-authored 20 publications receiving 30 citations. Previous affiliations of Adel R. Alharbi include University of Tabuk & Southern Methodist University.

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AES Based White Box Cryptography in Digital Signature Verification

TL;DR: White-box cryptosystems as mentioned in this paper have been used to protect the protected information and keys against black-box attacks and protect sensitive information in the context of white-box cryptographic primitives.
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Securing 5G-IoT Device Connectivity and Coverage Using Boltzmann Machine Keys Generation

TL;DR: In this paper, the authors proposed a Boltzmann machine (BMKG)-based encryption algorithm for securing 5G-enabled IoT device network environment and compared various asymmetric algorithms for key exchange.
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Cryptanalysis of Internet of Health Things Encryption Scheme Based on Chaotic Maps

TL;DR: In this article, the authors reported security flaws in the recently offered encryption technique based on a chaotic map for Internet of Health Things (IoHT) security and proposed some improvements to enhance the security of the understudy cryptographic algorithm.
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Predicting Rogue Content and Arabic Spammers on Twitter

Adel R. Alharbi, +1 more
- 30 Oct 2019 - 
TL;DR: This work collected a pure data set from spam accounts producing Arabic tweets, and applied lightweight feature engineering based on rogue content and user profiles to develop adaptive spam detection methods.
Journal ArticleDOI

IBOOST: A Lightweight Provably Secure Identity-Based Online/Offline Signature Technique Based on FCM for Massive Devices in 5G Wireless Sensor Networks

TL;DR: In this paper, the authors proposed a lightweight, provably secure identity-based online/offline signature technique (IBOOST) and its extension for massive devices in 5G-WSNs using fractional chaotic maps.