Explore a conference talk on generic and static detection of mobile malware using machine learning, focusing on Android but applicable to iOS. Learn about the rapid growth of smartphone adoption, the prevalence of Android devices, and the increasing threat of mobile malware. Discover the speaker's research on developing an effective solution to detect mobile threats using ML techniques. Gain insights into the methodology, including the use of neural networks, training processes, and the final workflow. Understand the results and implications of this approach for improving mobile security in an era of widespread smartphone usage and evolving cyber threats.
Generic and Static Detection of Mobile Malware Using ML
Hack In The Box Security Conference via YouTube
Overview
Syllabus
Introduction
Minhs background
Motivation
Alpha Station
In a nutshell
Inception
Neural Network
First Step
Second Step
Training
Final Workflow
Results
Summary
Conclusion
Taught by
Hack In The Box Security Conference
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