2020
DOI: 10.3390/fi12030044
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Abstract: This paper proposes a novel intrusion detection system (IDS), named RDTIDS, for Internet-of-Things (IoT) networks. The RDTIDS combines different classifier approaches which are based on decision tree and rules-based concepts, namely, REP Tree, JRip algorithm and Forest PA. Specifically, the first and second method take as inputs features of the data set, and classify the network traffic as Attack/Benign. The third classifier uses features of the initial data set in addition to the outputs of the first and the … Show more

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Cited by 155 publications
(46 citation statements)
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“…To detect these cyber-attacks in smart agriculture, security researchers have proposed intrusion detection systems based on machine learning and data mining algorithms. Ferrag et al [117] and Maglaras et al [127] designed a hybrid intrusion detection system, named RDTIDS, for internet-of-things networks, which can be applied for smart agriculture. Specifically, the RDTIDS system uses decision tree and rules-based concepts to classify the network traffic as attack/benign.…”
Section: F Intrusion Detection Systemsmentioning
confidence: 99%
“…To detect these cyber-attacks in smart agriculture, security researchers have proposed intrusion detection systems based on machine learning and data mining algorithms. Ferrag et al [117] and Maglaras et al [127] designed a hybrid intrusion detection system, named RDTIDS, for internet-of-things networks, which can be applied for smart agriculture. Specifically, the RDTIDS system uses decision tree and rules-based concepts to classify the network traffic as attack/benign.…”
Section: F Intrusion Detection Systemsmentioning
confidence: 99%
“…The experimental results show that it could achieve an accuracy rate over 0.95. Ferrag et al 17 focused on IoT environments, and introduced a combination of different classification approaches that are based on decision tree. The main limitation of these studies is the lack of real data sets in the evaluation part.…”
Section: Related Workmentioning
confidence: 99%
“…CR research teams should be focusing on improving various aspects of their testbeds. In addition, modern CRs should be enriched with novel features, such as various telecom-munication capabilities, emulated Banking systems, hospitals [81], simulated smart grids, automated vehicles [82], Virtual Cyber Centres of Operation, wireless sensor networks, real time Intrusion Detection Systems [83], honeypots [84], novel authentication mechanisms [85], mobile security scenarios, and several privacy mechanisms. By adding these features, new attack scenarios can be easily deployed on a testbed, revealing vulnerabilities of the various systems and thus giving the researchers the opportunity of developing innovative defence mechanisms.…”
Section: Challenges and Future Directionsmentioning
confidence: 99%