000			02640nam a22002417a 4500
003			FT8779
005			20251111102747.0
008			251111b ||||| |||| 00| 0 eng d
041			_aengtag
050			_aT58.4 P33 2025
082			_a.
100	1		_a Padlan, Wilton John B.; Tan, Luis Danile
245			_aValid: Fraud detection mobile application for government identity cards using optical character recognition and SHA-256 algorithm for data application
264		1	_a. _b. _cc2025
300			_bCapstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
336			_2text _atext _btext
337			_2unmediated _aunmediated _bunmediated
338			_2volume _avolume _bvolume
505			_aABSTRACT: Government-issued identification (ID) cards are essential for verifying individuals identities and granting access to various services. However, the increasing prevalence of ID-related fraud poses serious security challenges. This study presents ValID: A Fraud Detection Mobile Application for Government Identity Cards, which integrates Optical Character Recognition (OCR) for accurate text extraction and the Secure Hash Algorithm-256 (SHA-256) for preserving data integrity. Developed using the Agile Software Development Life Cycle (SDLC), the system showed 100% OCR accuracy in normal scanning conditions, ensuring reliable text recognition. Yet, under difficult scenarios such as handwritten, smudge, or blurry ID, the system’s OCR failed to extract data effectively, resulting in 0% accuracy. It also struggled with varying font styles and sizes, producing an average Character Error Rate (CER) of 64.25%, indicating a need for further enhancement in processing diverse formats. To support transparency and accountability, ValID includes an audit log feature that records all transactions. Meanwhile, SHA-256 ensures data protection by converting user inputs, like passwords, into complex hash values. For instance, a basic password such as “1234” is transformed into an irreversible alphanumeric string, safeguarding it from unauthorized access and tampering. Despite its promising results, ValID still has room for improvement. Future enhancements may include incorporating convolutional neural networks (CNNs) for more effective fraud detection, enabling real-time alerts for suspicious activity, and adding features like multi-factor authentication (MFA). Overall, ValID delivers a secure and efficient tool for combating government ID fraud, reinforcing trust in identity verification systems.
526			_aF
655			_aacademic writing
942			_2lcc _cMS
999			_c37061 _d37061