System and method of information retrieval from encrypted data files through a context-aware metadata ai engine

Abstract

This disclosure relates to personalized and dynamic server-side searching techniques for encrypted data. Current so-called 'zero-knowledge' privacy systems (i.e., systems where the server has ‘zero-knowledge’ about the client data that it is storing) utilize servers that hold encrypted data without the decryption keys necessary to decrypt, index, and/or re-encrypt the data. As such, the servers are not able to perform any kind of meaningful server-side search process, as it would require access to the underlying decrypted data. Therefore, such prior art ‘zero-knowledge’ privacy systems provide a limited ability for a user to search through a large dataset of encrypted documents to find critical information. Disclosed herein are communications systems that offer the increased security and privacy of client-side encryption to content owners, while still providing for highly relevant server-side search-based results via the use of content correlation, predictive analysis, and augmented semantic tag clouds for the indexing of encrypted data.