Kryptolab Protects Toss Facial Recognition Data with Homomorphic Encryption

Opening the Door to Next-Generation Security: Cryptolab Integrates Homomorphic Encryption Technology into Toss Facial Recognition! Cryptolab, a company specializing in homomorphic encryption, has partnered with fintech leader Toss to open new horizons in facial recognition security. Cryptolab successfully supplied Toss with its 'EFR (Encrypted Facial Recognition)' product, based on its core homomorphic encryption solution 'HEaaN'. This enables precise matching operations even when user facial feature point data is in an encrypted state. Homomorphic encryption, central to EFR, is an innovative technology that allows computations to be performed directly on encrypted data. This resolves the dilemma of data utilization in the age of AI. Previously, there was an inherent risk of original data exposure during AI training in cloud environments. However, homomorphic encryption allows sensitive information to be analyzed and processed securely without decryption, thus achieving both security and efficiency. Notably, Cryptolab's 'HEaaN' is unique because it implements a 4.5-generation algorithm that is over 100 times faster than existing homomorphic encryption technologies, thereby overcoming the limitations of real-time service application. This Toss case clearly demonstrates the potential for homomorphic encryption-based facial recognition technology to expand beyond finance into all industries where the protection of sensitive biometric information is essential, such as healthcare and the public sector. In the rapidly expanding biometric authentication market, including face payment and identity verification, Cryptolab's technology will establish itself as a key safeguard for protecting personal privacy. Building on this success, Cryptolab plans to further disseminate a next-generation security paradigm where data utilization and robust security coexist.