Harith. Al-Sahaf
Ian Welch
ABSTRACT
Feature selection and construction can potentially help reduce dimensionality and build more effective features that aim to improve performance. This paper utilises Genetic Programming (GP) to automatically select and construct high-level features for three cybersecurity-related tasks namely Ransomware detection, Spam detection, and Phishing website detection. The effectiveness of the features constructed by the proposed method has been assessed using three commonly-used machine learning algorithms on three datasets and compared against the performance of these machine learning algorithms applied to the original set of features and those features selected and constructed by another GP-based. The experimental results show that the proposed method has significantly improved the performance compared to the other methods.
- Soha Ahmed, Mengjie Zhang, and Lifeng Peng. 2013. Feature Selection and Classification of High Dimensional Mass Spectrometry Data: A Genetic Programming Approach. In Proceedings of the European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. Springer, 43--55. Google Scholar
Digital Library
- Krzysztof Krawiec. 2002. Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks. Genetic Programming and Evolvable Machines 3, 4 (2002), 329--343. Google ScholarDigital Library
- R. J. Nandi, A. K. Nandi, R. Rangayyan, and D. Scutt. 2006. Genetic Programming and Feature Selection for Classification of Breast Masses in Mammograms. In Proceedings of the 2006 International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 3021--3024.Google Scholar
- Kourosh Neshatian, Mengjie Zhang, and Mark Johnston. 2007. Feature Construction and Dimension Reduction Using Genetic Programming. In Proceedings of the Australasian Joint Conference on Artificial Intelligence. Springer, 160--170. Google ScholarDigital Library
- Binh Tran, Mengjie Zhang, and Bing Xue. 2017. Class Dependent Multiple Feature Construction Using Genetic Programming for High-Dimensional Data. In Proceedings of the Australasian Joint Conference on Artificial Intelligence. Springer, 182--194.Google ScholarCross Ref
Index Terms
- A genetic programming approach to feature selection and construction for ransomware, phishing and spam detection
Recommendations
A hybrid multiple feature construction approach for classification using Genetic Programming
AbstractThe purpose of feature construction is to create new higher-level features from original ones. Genetic Programming (GP) was usually employed to perform feature construction tasks due to its flexible representation. Filter-based ...
Highlights- A GP-based hybrid feature construction approach is developed.
- A multiple ...
Genetic programming for feature extraction and construction in image classification
AbstractGenetic Programming (GP) has been successfully applied to image classification and achieved promising results. However, most existing methods either address binary image classification tasks only or need a predefined classifier to ...
Highlights- A new GP representation to get an effective combination of features and classifiers.
Genetic Programming with a Genetic Algorithm for Feature Construction and Selection
The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we primarily examine the use of Genetic Programming and a Genetic Algorithm to pre-process data before it is ...
Comments