Exploring Algorithms For Data Extraction In Android Mobile Devices: A Detailed Survey

Abstract

With the widespread adoption of Android as the dominant mobile operating system, Android devices now store vast amounts of sensitive personal and organizational data. Extracting this data, whether for forensic investigations, data recovery, or cybersecurity purposes, has become a critical focus area. However, the complex nature of the Android ecosystem—marked by various versions, custom ROMs, encryption protocols, and security mechanisms—presents significant challenges for data extraction. This paper provides a comprehensive survey of the key algorithms and techniques used in extracting data from Android mobile phones. We explore methods including Android Debug Bridge (ADB)-based extraction, memory dumping, file system traversal, SQLite database parsing, and cloud-based extraction. The survey also covers advanced techniques such as JTAG, chip-off extraction, and data carving algorithms used in recovering deleted or inaccessible data. For each algorithm, we assess strengths, limitations, and applicability in different scenarios, including forensic investigations and real-time data recovery. Furthermore, we address the challenges posed by encryption, fragmented file systems, and Android version fragmentation. Finally, the paper highlights future research directions for enhancing extraction accuracy, speed, and legal compliance, particularly in the face of growing data protection regulations.