M
Makhlouf Derdour
Researcher at University of Pau and Pays de l'Adour
Publications - 48
Citations - 1072
Makhlouf Derdour is an academic researcher from University of Pau and Pays de l'Adour. The author has contributed to research in topics: Computer science & Intrusion detection system. The author has an hindex of 6, co-authored 42 publications receiving 484 citations. Previous affiliations of Makhlouf Derdour include Life University & University of Annaba.
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Journal ArticleDOI
Blockchain Technologies for the Internet of Things: Research Issues and Challenges
Mohamed Amine Ferrag,Makhlouf Derdour,Mithun Mukherjee,Abdelouahid Derhab,Leandros A. Maglaras,Helge Janicke +5 more
TL;DR: A comprehensive survey of the existing blockchain protocols for the Internet of Things (IoT) networks is presented in this article, where the authors provide a classification of threat models, which are considered by blockchain protocols in IoT networks, into five main categories, namely identity-based attacks, manipulation based attacks, cryptanalytic attacks, reputation based attacks and service based attacks.
Journal ArticleDOI
Blockchain Technologies for the Internet of Things: Research Issues and Challenges
Mohamed Amine Ferrag,Makhlouf Derdour,Mithun Mukherjee,Abdelouahid Derhab,Leandros A. Maglaras,Helge Janicke +5 more
TL;DR: A comprehensive survey of the existing blockchain protocols for the Internet of Things (IoT) networks and a side-by-side comparison of the state-of-the-art methods toward secure and privacy-preserving blockchain technologies with respect to the blockchain model.
Journal ArticleDOI
RDTIDS: Rules and Decision Tree-Based Intrusion Detection System for Internet-of-Things Networks
TL;DR: The experimental results obtained by analyzing the proposed RDTIDS using the CICIDS2017 dataset and BoT-IoT dataset, attest their superiority in terms of accuracy, detection rate, false alarm rate and time overhead as compared to state of the art existing schemes.
Proceedings ArticleDOI
A Novel Hierarchical Intrusion Detection System Based on Decision Tree and Rules-Based Models
TL;DR: In this paper, the authors proposed a novel intrusion detection system (IDS) that combines different classifier approaches which are based on decision tree and rules-based concepts, namely, REP Tree, JRip algorithm and Forest PA.
Posted Content
A Novel Hierarchical Intrusion Detection System based on Decision Tree and Rules-based Models.
TL;DR: The experimental results obtained by analyzing the proposed IDS using the CICIDS2017 dataset, attest their superiority in terms of accuracy, detection rate, false alarm rate and time overhead as compared to state of the art existing schemes.