A distributed algorithm for Android malware detection - دانشکده فنی و مهندسی
A distributed algorithm for Android malware detection
نوع: Type: thesis
مقطع: Segment: masters
عنوان: Title: A distributed algorithm for Android malware detection
ارائه دهنده: Provider: Mohammadali Eftekhari
اساتید راهنما: Supervisors: dr Morteza Yousef Sanati
اساتید مشاور: Advisory Professors:
اساتید ممتحن یا داور: Examining professors or referees: dr Muharram Mansoorizadeh- dr vahid nosrati
زمان و تاریخ ارائه: Time and date of presentation: 2024
مکان ارائه: Place of presentation: Faculty of Engineering
چکیده: Abstract: social networking, and diverse business operations, which puts their personal information at risk due to the vulnerabilities of the Android operating system. The rapid development of Android malware has caused many traditional malware detection methods to lose their accuracy. Research indicates that machine learning is an effective method for detecting malware. The swift evolution of malware decreases the accuracy of trained models over time. Additionally, collecting malware-related data from Android devices compromises user privacy. To address this issue, this paper utilizes incremental and federated learning. Recently, federated learning has been introduced for training machine learning models on decentralized devices to preserve privacy. This paper employs a Multi-Layer Perceptron (MLP) within the federated learning framework. Incremental learning is achieved using the stacking method, a type of ensemble learning. The result of this research is a model with an accuracy of 99.52%, which, compared to existing methods, demonstrates a significant improvement in computational time complexity while enhancing learning quality and model accuracy
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