Homomorphic Encryption

Homomorphic encryption is a cryptographic technique that allows computations to be performed on encrypted data without requiring access to the plaintext. This means that data can remain encrypted while still being processed, enabling users to perform operations such as addition and multiplication directly on the ciphertext. The result of these operations, when decrypted, will match the result of operations performed on the original plaintext data.This is particularly useful in scenarios where sensitive data needs to be processed by third parties, such as in cloud computing or secure data analysis, without exposing the underlying data to those parties. Homomorphic encryption ensures privacy and confidentiality while enabling meaningful computations, thus facilitating secure data sharing and outsourcing of computation tasks. It is categorized into three types: partially homomorphic encryption (which supports a limited set of operations), somewhat homomorphic encryption (which can handle multiple operations but is limited by the complexity of the computations), and fully homomorphic encryption (which supports arbitrary computations on encrypted data).
Revolutionary Technology! How Machines Learn Like Humans Now

Revolutionary Technology! How Machines Learn Like Humans Now

Machine learning is increasingly becoming the cornerstone of new technologies, revolutionizing how we interact with the digital world. But what exactly is this buzzword, “machine learning,” in simple terms? At its core, machine learning is all about enabling computers to learn from
December 21, 2024