Secure Image Publishing System Using Facial Identity Verification

Abstract

With The Rapid Growth Of Social Media Platforms, Unauthorized Sharing And Misuse Of Personal Images Has Become A Major Privacy Concern. Many Users Upload Photos Containing Other Individuals Without Their Permission, Which May Lead To Privacy Violations And Identity Misuse. This Paper Proposes A Secure Image Publishing System Using Facial Identity Verification That Detects Faces In Uploaded Images And Verifies Whether The Person In The Image Has Granted Permission For The Upload. The System Uses Computer Vision Techniques To Detect Faces And Compare Them With Registered User Data Stored In A Secure Database. If A Match Is Found, The System Sends A Notification To The Identified Person And Requests Approval Before Allowing The Image To Be Published. The Proposed System Integrates Technologies Such As Python, OpenCV, And Machine Learning–based Face Recognition To Ensure Accurate Identification And Permission Control. By Introducing An Automated Permission Mechanism, The System Helps Prevent Unauthorized Photo Sharing And Enhances Privacy Protection On Social Media Platforms. Experimental Results Demonstrate That The System Can Effectively Detect Faces And Manage Image Ownership Permissions With Reliable Performance.

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