## 1 Introduction
The process of extracting SQLite evidence in FORC involves using the header of the SQLite file and the file extension, which allows for automatic extraction of the relevant files. By utilizing a 16-byte hexadecimal \"magic\" header string, \"53 51 4c 69 74 65 20 66 67 72 6d 61 74 20 33 00\", FORC is able to identify and extract all SQLite files created, generated, or revised by the application. Comparative evaluations with other popular forensic tools such as Belkasoft, Magnet AXIOM, and FINALMobile, demonstrate that FORC outperforms these tools in identifying and extracting SQLite files from Android devices. This suggests that FORC has the potential to significantly enhance the efficiency and accuracy of mobile forensic investigations. This research not only introduces a practical and efficient solution for SQLite evidence extraction in Android devices but also lays the groundwork for standardization and future advancements in mobile forensic techniques. It addresses the pressing need for automation and reliability in digital forensics, both of which ultimately benefit law enforcement agencies and organizations involved in forensic investigations. The research significantly contributes to the field of digital forensics by addressing critical challenges and advancements related to the extraction of SQLite evidence from mobile devices, with a particular focus on Android smartphones. The contributions of this research can be summarized as follows:  
* Automated Tool Development: The research introduces a novel automated tool called FORC which is designed to streamline the process of mobile forensic data acquisition, analysis, and reporting. FORC employs a header-based and file-extension-based approach for the automatic extraction of SQLite files, enhancing the efficiency and accuracy of digital forensic investigations. * Enhanced Efficiency: By utilizing FORC, investigators can automate certain aspects of the forensic investigation process, reducing manual effort and the potential for human errors. This automation is crucial in coping with the increasing use of mobile devices and the growing volume of data that requires analysis. * Improved Extraction Accuracy: Comparative evaluations of FORC against popular forensic tools like Belkasoft, Magnet AXIOM, and FINALMobile demonstrate its supe rior performance in identifying and extracting SQLite files from Android devices. This enhancement in extraction accuracy contributes to more reliable and comprehensive forensic investigations. * Addressing Standardization: The research highlights the need for standardization in the extraction of SQLite evidence from mobile devices. While this paper focuses on Android devices, the proposed framework and automated tool can serve as a foundation for standardized approaches that can be applied across various mobile platforms, ensuring consistent and reliable results in digital forensic investigations. * Future Research Directions: The research identifies several areas that require further investigation, including performance evaluation, privacy and security implications, automation, applicability to different devices and operating systems, and the handling of challenges posed by big data in digital forensics. These areas provide opportunities for future research and innovation in the field.