Darkshield: Mobile Intrusion Detection using Post-Authentication Failure Analysis and Android Security APIS
DOI:
https://doi.org/10.15662/IJARCST.2026.0903005Keywords:
Smartphone security, mobile theft detection, intrusion detection, offline SMS alert, face recognition, SIM change detection, GPS tracking, Cloudinary, Android securityAbstract
Smartphones store sensitive personal, financial, and confidential data, making them frequent targets for theft and unauthorized access. Traditional security methods such as PINs, passwords, and biometrics mainly prevent entry but offer limited protection after repeated intrusion attempts. This paper presents DarkShield, an Android-based intrusion detection and anti-theft system that proactively detects suspicious unlock attempts and alerts the rightful owner. When multiple incorrect PIN or password entries are detected, the system captures the intruder’s image, retrieves the current GPS location, uploads the evidence to cloud storage, and sends alerts through SMS and email. SMS notifications include the location and image link, while emails contain location details and the captured image as an attachment. The system also supports offline SMS alerts, online email notifications, and SIM change detection for unauthorized SIM replacement. To reduce false alerts, a machine learning-based face recognition module verifies whether the captured face matches the authorized user. By integrating evidence capture, location tracking, dual alert mechanisms, SIM monitoring, and intelligent face verification, DarkShield provides an effective solution for smartphone theft detection and unauthorized access prevention.
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