Description: Homomorphic encryption is a type of encryption that allows operations to be performed on encrypted data without needing to decrypt it. This means calculations can be carried out and valid results obtained, all while the data remains encrypted. This approach is particularly valuable in contexts where data privacy and security are paramount, such as in cloud computing and processing sensitive information. Homomorphic encryption is classified into three types: partially homomorphic, fully homomorphic, and leveled homomorphic, depending on the complexity of the operations that can be performed. Its main feature is that performing operations on encrypted data yields results that, when decrypted, are the same as if they had been performed on the original data. This opens up a range of possibilities for protecting information, allowing organizations to process data without compromising its confidentiality. As technology advances, homomorphic encryption is becoming an essential tool for ensuring information security in an increasingly digital world.
History: The concept of homomorphic encryption was first introduced by mathematician and cryptographer Craig Gentry in his doctoral thesis in 2009. Gentry proposed an encryption scheme that allowed operations to be performed on encrypted data, representing a significant advancement in the field of cryptography. Since then, research in homomorphic encryption has grown, with various advancements and improvements in the efficiency and applicability of these methods. In 2014, the first fully functional homomorphic encryption system was presented, marking an important milestone in its development.
Uses: Homomorphic encryption is primarily used in cloud computing, where sensitive data can be processed without being exposed. It is also applied in the healthcare sector, allowing for the analysis of medical data without compromising patient privacy. Additionally, its use is being explored in fields like electronic voting systems and the protection of financial data.
Examples: A practical example of homomorphic encryption is the systems developed by various organizations, which allow calculations to be performed on encrypted data in the cloud. Another case is the use of homomorphic encryption in data analysis platforms, where statistical operations can be performed on sensitive data without revealing it. Research has also been conducted on its application in voting systems, where votes can be counted without being decrypted.
