Abstract
Handling superfluous and insignificant features in high-dimension data sets incidents led to a long-term demand for system anomaly detection. Ignoring such elements with spectral instruction not speeds up the analysis process but again facilitates classifiers to make accurate selections during attack perception stage, when wrestling with huge-scale and heterogeneous data. In this paper, for dimensionality reduction of data, we use Correlation-based Feature Selection (CFS) and Naïve Bayes (NB) classifier techniques. The proposed Intrusion Detection System (IDS) classifies attacks using a Multilayer Perceptron (MLP) and Instance-Based Learning algorithm (IBK). The accuracy of the introduced IDS is 99.87% and 99.82% with only 5 and 3 features out of 78 features for IBK. Other metrics such as precision, Recall, F-measure, and Receiver Operating Curve (ROC) also confirm the principal performance of IBK compared to MLP.
| Original language | English |
|---|---|
| Title of host publication | 2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET) |
| Publisher | IEEE |
| Pages | 49-53 |
| Number of pages | 5 |
| ISBN (Electronic) | 9780738105277 |
| ISBN (Print) | 9781665423007 |
| DOIs | |
| Publication status | Published - 21 Jan 2021 |
| Event | IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI - Online Duration: 14 Dec 2020 → 16 Dec 2020 https://honet-ict.org/archives/honet20/index.html (Link to conference website) |
Publication series
| Name | |
|---|---|
| ISSN (Print) | 1949-4092 |
| ISSN (Electronic) | 1949-4106 |
Conference
| Conference | IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI |
|---|---|
| Abbreviated title | IEEE HONET 2020 |
| Period | 14/12/20 → 16/12/20 |
| Internet address |
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Keywords
- intrusion detection system (IDS)
- correlation-based feature (CFS)
- classifier subset evaluation
- multilayer perceptron (MLP)
- instance-based learning algorithm (IBK)
ASJC Scopus subject areas
- Information Systems and Management
- Artificial Intelligence
- Information Systems
- Energy Engineering and Power Technology
- Computer Networks and Communications
- Computer Science Applications
- Renewable Energy, Sustainability and the Environment
Documents and Links
- Ali, A. et al (2020) Network intrusion detection leveraging machine learning and feature selection
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