Enhancing Ransomware Detection: An  Ensemble Learning Approach

Ananth Rajesh; Indu verma

Enhancing Ransomware Detection: An Ensemble Learning Approach

May 2024

Vol-10, Issue-3

Paper ID: 23899

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Machine learning, Ransomware detection

Keywords

Ransomware Ensemble learning Machine learning Decision tree Random forest AdaBoost XGBoost Gradient boosting.

Abstract

Ransomware attacks are a major cybersecurity threat. They target organizations of all types and extort money from them. Machine learning (ML) is a promising way to improve ransomware detection. This research builds and tests an ensemble learning ML model for ransomware detection. The model uses Decision Trees, Random Forests, AdaBoost, XGBoost, Gradient Boosting, and a Voting Classifier. Experiments prove the efficiency of the ensemble model in detecting ransomware, outperforming individual classifiers. The ensemble model consistently exhibits excellent performance on all evaluation metrics, effectively distinguishing ransomware from benign software. This highlights the potential of ensemble learning in improving ransomware identification, thereby strengthening cybersecurity measures. Future research should focus on optimizing ensemble configurations and continuously evaluating model performance against emerging ransomware variants. This study enhances cybersecurity resilience by strengthening defenses against ransomware attacks and minimizing their consequences on businesses and individuals.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Ananth Rajesh	Christ University
2	Indu verma	Christ University

How to Cite

Use the following formats to cite this article in your research.

APA Style

Rajesh, Ananth & verma, Indu (2024). Enhancing Ransomware Detection: An Ensemble Learning Approach. International Journal of Advance Research and Innovative Ideas In Education, 10(3), 1985-1993.

MLA Style

Rajesh, Ananth, and Indu verma. "Enhancing Ransomware Detection: An Ensemble Learning Approach." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, 2024, pp. 1985-1993.

IEEE Style

Ananth Rajesh and Indu verma, "Enhancing Ransomware Detection: An Ensemble Learning Approach," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, pp. 1985-1993, 2024.

Vancouver Style

Rajesh Ananth, verma Indu. Enhancing Ransomware Detection: An Ensemble Learning Approach. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(3):1985-1993.

Harvard Style

Rajesh, Ananth & verma, Indu (2024) 'Enhancing Ransomware Detection: An Ensemble Learning Approach', International Journal of Advance Research and Innovative Ideas In Education, 10(3), pp. 1985-1993.

Chicago Style

Rajesh, Ananth and Indu verma. "Enhancing Ransomware Detection: An Ensemble Learning Approach." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 1985-1993.

Turabian Style

Rajesh, Ananth and Indu verma. "Enhancing Ransomware Detection: An Ensemble Learning Approach." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 1985-1993.