AMA on X

Original author: Advait (Leo) Jayant Compilation: LlamaC "Recommended message: Fully Homomorphic Encryption (FHE) is often hailed as the holy grail of cryptography. This article explores the prospects of FHE in the field of artificial intelligence, pointing out the current limitations. It also lists some projects dedicated to using fully homomorphic encryption (FHE) in the field of encryption for AI applications. For Crypto enthusiasts, this article provides an in-depth understanding of Fully Homomorphic Encryption. Enjoy!" Main text👇 A wants highly personalized recommendations on Netflix and Amazon. B doesn't want Netflix or Amazon to know their preferences. In today's digital age, we enjoy Amazon and Netflix.

Written by: Davide

AI + web3, worth looking forward to?

Fully homomorphic encryption (FHE) allows calculations on encrypted data without decryption, promising to resolve the privacy and transparency paradox in blockchain. Despite challenges in computational efficiency and secret key management, FHE is attracting investment and rapidly developing, with significant progress expected in the next 3-5 years.

Fully Homomorphic Encryption (FHE): Introduction and Application Scenarios The term "encryption" usually evokes thoughts of static encryption and encryption in transit. Static encryption stores data in an encrypted form on hardware devices or cloud servers, accessible only to authorized personnel who can view the decrypted content. Encryption in transit ensures that data transmitted over the internet can only be interpreted by designated recipients; even if the data passes through public routers or channels, intermediaries cannot decrypt it. Both scenarios rely on encryption algorithms and additionally ensure data integrity. "Authenticated encryption" not only prevents unauthorized decryption of ( confidentiality ), but also prevents man-in-the-middle attacks from tampering with the ciphertext ( integrity/authenticity ). Certain multi-party collaboration scenarios require complex processing of ciphertext, which falls under the category of privacy protection technology. Fully Homomorphic Encryption ( FHE ) is one of them. Taking online voting as an example: voters encrypt their voting results and submit them to an intermediary entity, which aggregates all results and calculates the number of votes for each candidate, most