Deep Learning-Based Android Malware Detection with CNN-GRU Model

Kalathil Salim, Harisankar (2024) Deep Learning-Based Android Malware Detection with CNN-GRU Model. Masters thesis, Dublin, National College of Ireland.

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Abstract

Android malware presents substantial security hazards to mobile users worldwide, jeopardizing personal, financial, and device data. Given the exponential increase in these dangers, it is imperative to implement effective detection systems to safeguard consumers and preserve the integrity of the smartphone ecosystem. Conventional approaches frequently lack strong security measures because of the ever-changing characteristics of malicious software. Therefore, advanced techniques based on deep learning have emerged as promising approaches to enhance detection accuracy and efficiency, this study developed a sophisticated hybrid detection model using Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU) to classify Android applications as either benign or malicious, thereby contributing to the ongoing effort against mobile malware threats. The research involved preprocessing the dataset in four distinct ways, including SMOTE and Chi-square to address imbalance and optimize feature selection. The result demonstrated that the developed CNN-GRU model achieved superior performance with the highest accuracy of 99% accuracy surpassing several existing models.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Sahni, Vikas UNSPECIFIED
Uncontrolled Keywords:	CNN-GRU Model; SMOTE; Chi-square
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	30 Jul 2025 10:00
Last Modified:	30 Jul 2025 10:00
URI:	https://norma.ncirl.ie/id/eprint/8327

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