Published Paper Details:

As virtual statistics turns into an increasing number of popular ensuring strong safety for sensitive files is critical this studies introduces a complicated protection framework that mixes biometric watermarking with device mastering to establish a tamper-resistant and adaptive protection system by way of encoding intricate iris and fingerprint patterns the usage of a custom designed rubiks cube encryption algorithm the method creates a comfy embedded watermark that is tremendously proof against manipulation in parallel convolutional neural networks CNNs examine and authenticate biometric statistics permitting real-time detection of spoofing tries and unauthorized changes the adaptive gaining knowledge of functionality of CNNs lets in the system to refine its detection accuracy through the years strengthening its resilience against rising threats this precise integration of encryption and shrewd pattern recognition gives extensive improvements in file security with ability packages in sectors which include healthcare finance and authorities wherein records integrity and authentication are paramount.