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ISSN 2561-8156 (Online) - ISSN 2561-8148 (Print)
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Volume 7 Issue 3 pp. 1241-1248, 2023

Authors: Mohammad Al Rawajbeh, Wael Alzyadat, Khalid Kaabneh, Suha Afaneh, Dima Farhan Alrwashdeh, Hamdah Samih Albayaydah, Issam Hamad AlHadid

📋 Author Affiliations:
M. Al Rawajbeh ORCID 1, W. Alzyadat ORCID 1, K. Kaabneh2, S. Afaneh ORCID 3, D.F. Alrwashdeh ORCID 4, H.S. Albayaydah5, I.H. Alhadid ORCID 4
1 Faculty of Science and Information Technology, Al Zaytoonah University of Jordan, Amman, Jordan
2 Faculty of Information Technology, Al-Ahliyya Amman University, Amman, Jordan
3 Faculty of Information Technology, Zarka University, Zarka, Jordan
4 Faculty of Information Technology and Systems, University of Jordan, Aqaba, Jordan
5 MIS, Faculty of MIS, Aqaba University of Technology, Aqaba, Jordan
19 Source: Scopus
Crossref 16 Source: CrossRef

🔑 Keywords: Internet of Things, Technology, Security Analysis, Anomaly detection system, Cybersecurity

Abstract: In the era of IoT gaining traction, attacks on IoT-enabled devices are the order of the day that emanates the need for more protected IoT networks. IoT's key feature deals with massive amounts of data sensed by numerous heterogeneous IoT devices. Numerous machine learning techniques are used to collect data from different types of sensors on the objects and transform them into information relevant to the application. Furthermore, business and data analytics algorithms help in event prediction based on observed behavior and information. Routing information securely over the internet with limited resources in IoT applications is a key problem. The study proposes a model for detecting network anomalies in IoT devices to enhance the security of the devices. The study employed the IoT Botnet dataset, and K-fold cross-validation tests were used for validating the values of evaluation metrics. The average values of Accuracy, Precision, Recall, and F Score was 97.4.

How to cite this paper
APA: Rawajbeh, M., Alzyadat, W., Kaabneh, K., Afaneh, S., Alrwashdeh, D., Albayaydah, H & AlHadid, I. (2023). A new model for security analysis of network anomalies for IoT devices. International Journal of Data and Network Science, 7(3), 1241-1248.
Chicago/Turabian: Rawajbeh, M., Alzyadat, W., Kaabneh, K., Afaneh, S., Alrwashdeh, D., Albayaydah, H & AlHadid, I. 2023. "A new model for security analysis of network anomalies for IoT devices." International Journal of Data and Network Science 7, no. 3 (2023): 1241-1248.
AMA: Rawajbeh, M., Alzyadat, W., Kaabneh, K., Afaneh, S., Alrwashdeh, D., Albayaydah, H & AlHadid, I. A new model for security analysis of network anomalies for IoT devices. International Journal of Data and Network Science. 2023;7(3):1241-1248.

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📚 Journal: International Journal of Data and Network Science | 📅 Year: 2023 | 📖 Volume: 7 | 📄 Issue: 3 | 👁️ Views: 1413 | 📊 Crossref: 16

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