Privacy Risk Detection System for Social Media
Keywords:
Deep processing, Image processing, Named entity recognition, Natural Language Processing (NLP), Topic modellingAbstract
Nowadays, Social media has become an essential part of daily life, as it allows individuals to share their ideas, experiences, and personal movements with all users; however, it sometimes poses privacy risks or threats by revealing personal information. Users usually post images, videos, and text without realizing that this might reveal personal or sensitive information, such as location, Personal Identification Numbers, or details that could be exploited. This project will help to present an AI powered Application that will detect and alert users about privacy risk that will be caused by sharing posts on social media. This system will use the concept of Deep Learning, Natural Language Processing (NLP), and also Image Processing techniques to analyze both visual and textual data. It scans uploaded media for features like faces, license plates, geotags, documents, or background elements that may expose personal data. It also analyses captions and comments for mentions of sensitive information such as phone numbers, addresses, or plans that may attract malicious intent. The latest NLP and deep learning methods, like Named Entity Recognition, transformer-based detection, stylometry, topic modelling, privacy-preserving learning, Autoencoders, CNNs (Convolutional Neural Networks), LSTM- based Anomaly Detection, and AI-Powered Image Anonymization, are used. After the risk is detected, the scanner gives the real-time suggestions or warnings before the post is uploaded. This tool is designed to be user-friendly and works by allowing seamless privacy checks without interrupting the user experience. The main objective of this project is to encourage responsible sharing by making users more aware of the consequences of posts. It serves as a proactive approach to digital privacy, aiming to reduce cases of identity theft, stalking, and data misuse on social media platforms. With increasing threats to personal data, this solution brings much- needed attention to privacy awareness in the online world.
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