Holistic Smartphone Data Protection System Integrating Android App Analysis And Secure Metadata Tracking

Abstract

This Project Aims To Design A *Comprehensive Smartphone Data Security System* To Enhance Security Of Android Phone By Smart Malware Detection And Metadata Management. With The Increased Use Of Mobile Devices For Critical Applications Such As Telephony And Banking, Traditional Signaturebased Security Tools Are No Longer Effective To Identify Advanced Types Of Malware Like Zero-day And Polymorphic Attacks. Our System Addresses These Issues By Employing A Machine Learning Based Model Using XGBoost Algorithm To Detect Malware Android Apps By Considering Both Static And Dynamic Features, Such As Permissions, API Calls And Usage Patterns. This Enables Efficient Detection Of Malicious Apps With Minimal False Positives. In Addition, We Implement A Blockchain-like JSON-based Module To Ensure Data Integrity And Transparency, By Storing The Detection Results And Information About The Model. This Guarantees Integrity And Allows Pre-installation Authentication Of Apps. Our System Also Incorporates Other Important Components Such As A Malware Level Indicator And A Proactive Blocker To Prevent The Installation Or Distribution Of Critical Applications. Overall, Our System Provides A Scalable, Real-time And Efficient System To Improve Mobile Security Against The Ever-evolving Threats.

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