Malware Detection

Malware Detection

P. Pranay, T. Pranay, V. Pranay, K. Praneeth, G. Praneeth, M. Praneeth, Prof. T. Ramya

Department of CSE(AIML) ,

MALLA REDDY UNIVERSITY HYDERABAD

Abstract: The "Malware Detection on Application using Machine Learning" project is a focused initiative aimed at enhancing the security of mobile applications through advanced detection mechanisms. As the threat landscape for mobile app-based malware continues to evolve, this project leverages the power of machine learning to develop robust and adaptive detection models. The project involves the analysis of application behavior, employing both static and dynamic approaches, to identify and categorize potential malware instances. By training machine learning models on extensive datasets, the project aims to enable the detection of diverse forms of malicious software, including viruses and trojans. The integration of machine learning into the detection process facilitates continuous learning and adaptation to emerging threats.
Keywords: Malware Detection, Machine Learning, Mobile Applications, Security Enhancement, Threat Landscape, Behavioral Analysis, Static Analysis, Dynamic Analysis, Virus Detection, Trojan Detection, Adaptive Models, Continuous Learning, Emerging Threats, Proactive Defense, Mobile App Security.