Automated Intelligent Redaction System for Personally Identifiable Information in Identity Card Screenshots

The popularity of screenshots that include government-issued identity documents for circulation, sharing, or storage is a huge privacy risk, as these images are frequently redacted improperly. Manual redaction methods are usually inconsistent, time-consuming, and prone to human error. In an attempt to overcome these problems, the present study presents an automated screenshot redaction tool that can identify and mask sensitive information like ID numbers, names, dates of birth, and photographs across various document formats. Through the integration of deep learning-based object detection and optical character recognition (OCR) with real-time processing power, screenshots are processed and redacted. Experimental results on a wide range of ID screenshots achieve 95.6 % detection accuracy and less than one second of processing time per image. This system provides a solid solution for any sector that handles sensitive identification data, and digital workflows using this system greatly improve privacy compliance. It automates the redaction, improving efficiency, decreasing human error, and enhancing privacy protection in the environment where there is usually sharing or storage of personal data

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Published
2025-08-04
DOI
https://doi.org/10.1109/icscsa66339.2025.11170735
Primary Topic
Cognitive Computing and Networks
Type
article
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article

Automated Intelligent Redaction System for Personally Identifiable Information in Identity Card Screenshots

Thirupathi Krishna Sowmya, S. Aruna Deepthi, G. Mounika, Saravana Sai Garapati et al.
Cognitive Computing and Networks
article

Automated Intelligent Redaction System for Personally Identifiable Information in Identity Card Screenshots

Thirupathi Krishna Sowmya, S. Aruna Deepthi, G. Mounika, Saravana Sai Garapati, Upadrasta Vamshi Krishna
article en

Abstract

The popularity of screenshots that include government-issued identity documents for circulation, sharing, or storage is a huge privacy risk, as these images are frequently redacted improperly. Manual redaction methods are usually inconsistent, time-consuming, and prone to human error. In an attempt to overcome these problems, the present study presents an automated screenshot redaction tool that can identify and mask sensitive information like ID numbers, names, dates of birth, and photographs across various document formats. Through the integration of deep learning-based object detection and optical character recognition (OCR) with real-time processing power, screenshots are processed and redacted. Experimental results on a wide range of ID screenshots achieve 95.6 % detection accuracy and less than one second of processing time per image. This system provides a solid solution for any sector that handles sensitive identification data, and digital workflows using this system greatly improve privacy compliance. It automates the redaction, improving efficiency, decreasing human error, and enhancing privacy protection in the environment where there is usually sharing or storage of personal data

Vignana Jyothi Institute of Management (IN)
Openalex Percentile: Top 86%
Cognitive Computing and Networks
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Automated Intelligent Redaction System for Personally Identifiable Information in Identity Card Screenshots — Thirupathi Krishna Sowmya, S. Aruna Deepthi, et al. · (2025) | TGRS Research Map | TGRS