Homomorphic Encryption

What is Homomorphic Encryption?

Homomorphic encryption is revolutionizing the artificial intelligence (AI) industry by ensuring data privacy and security. It allows AI models to process encrypted data and generate encrypted results, which can then be decrypted by the data owner. This means that sensitive data, such as medical records or financial information, can be used to train AI models without exposing the raw data itself. This approach not only safeguards personal information but also complies with stringent data protection regulations. By enabling secure data sharing and collaboration, homomorphic encryption opens up new possibilities for industries like healthcare, finance, and beyond, where data sensitivity is paramount.

A form of encryption that allows computations to be performed on encrypted data without needing to decrypt it first.

Examples

• Healthcare: A hospital can use homomorphic encryption to allow researchers to analyze patient data to find patterns or make predictions about health outcomes, all while keeping the patient's personal data secure.


• Finance: Financial institutions can use homomorphic encryption to perform risk analysis on encrypted customer data, ensuring that sensitive information remains private while still gaining valuable insights.

Additional Information

• Homomorphic encryption supports various types of operations, including addition and multiplication, on encrypted data.


• It is a computationally intensive process, but advances in technology are making it increasingly feasible for real-world applications.