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All Journal International Journal of Electrical and Computer Engineering JOIN (Jurnal Online Informatika)
Alshraiedeh, Fuad
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Computer Science & IT Electrical & Electronics Engineering

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Optimizing intrusion detection in 5G networks using dimensionality reduction techniques Salah, Zaher; Elsoud, Esraa; Al-Sit, Waleed; Alhenawi, Esraa; Alshraiedeh, Fuad; Alshdaifat, Nawaf
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5652-5671

Abstract

The proliferation of internet of things (IoT) technologies has expanded the user base of the internet, but it has also exposed users to increased cyber threats. Intrusion detection systems (IDSs) play a vital role in safeguarding against cybercrimes by enabling early threat response. This research uniquely centers on the critical dimensionality aspects of wireless datasets. This study focuses on the intricate interplay between feature dimensionality and intrusion detection systems. We rely on the renowned IEEE 802.11 security-oriented AWID3 dataset to implement our experiments since AWID was the first dataset created from wireless network traffic and has been developed into AWID3 by capturing and studying traces of a wide variety of attacks sent into the IEEE 802.1X extensible authentication protocol (EAP) environment. This research unfolds in three distinct phases, each strategically designed to enhance the efficacy of our framework, using multi-nominal class, multi-numeric class, and binary class. The best accuracy achieved was 99% in the three phases, while the lowest accuracy was 89.1%, 60%, and 86.7% for the three phases consecutively. These results offer a comprehensive understanding of the intricate relationship between wireless dataset dimensionality and intrusion detection effectiveness.
Using Readability Metrics in Estimating the Readability of REpresentational State Transfer State Transfer Uniform Resource Identifiers Schema Alshraiedeh, Fuad; Katuk, Norliza; Almahasneh, Hossam
JOIN (Jurnal Online Informatika) Vol 11 No 1 (2026)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v11i1.1653

Abstract

Uniform Resource Identifiers (URIs) may have a direct impact on the understanding of REpresentational State Transfer State Transfer (RESTful) functionality, and thus, on the discovery of final RESTful product. RESTful Web Services (WS)/Application Programming Interfaces (APIs) are designed to expose data and functionality through resources accessed by dedicated URIs over HyperText Transfer Protocol (HTTP), which recently represents the direct descriptions schema of what functions does the concerned RESTful WS/API present. Furthermore, the discovery of suitable RESTful is heavily rely on the simplicity of understanding their URI schemas, which recently suffer from critical issues in how to measure their readability. For that, WS/APIs developers aspire to measure the readability of RESTful URI schemas before exposing them over the Internet to estimate their usability. Consequently, this research proposes four readability metrics for the stated purpose namely: Flesch-Kincaid (F-K), Flesch Reading Ease (FRES), Simple Measure of Gobbledygook (SMOG), and Coleman Liau Index (CLI). The research identifies the variables required to calculate the readability metric and formulate the equations for them. Four experts in linguistics were asked to validate the proposed metrics and their identified variables. The research successfully conducted empirical research on 8 well-known RESTful WSs/APIs of the dataset, and the proposed metrics were implemented on 6952 URIs schemas. The average values for the aforementioned metrics were 7.41%, 59.63%, 6.73%, and 17.55% respectively, where in certain metrics, a low average value signifies easy readability, but in others, it signifies hard readability, and vice versa.
Co-Authors Al-Sit, Waleed Alhenawi, Esraa Almahasneh, Hossam Alshdaifat, Nawaf Elsoud, Esraa Katuk, Norliza Salah, Zaher