Can we protect our secrets from the coming quantum computer threat?

Cultures · Published 11 October 2026 Swipe more like this →

In short: As quantum computing advances, current encryption may become obsolete. To counter this, NIST has standardized ML-KEM, a post-quantum key-encapsulation mechanism. It uses complex mathematical lattice problems to establish shared secrets, ensuring that even a powerful quantum adversary cannot decrypt your private communications.

ML-KEM, formerly known as Kyber, is a key-encapsulation mechanism (KEM) designed to establish a shared secret key between two parties over a public channel. Once this secret is established, it can be used with symmetric-key algorithms for secure encryption and authentication. This mechanism's protection depends on how hard it is to solve the Module Learning with Errors (M-LWE) problem, which is a version of the learning with errors lattice problem. This specific lattice-based approach offers advantages in terms of key material size and ciphertext length compared to competing methods. It was originally developed by researchers from North America and Europe.

The standard, formalized as FIPS 203 in 2024, offers three distinct parameter sets to balance security and performance. ML-KEM-512 provides NIST security level 1, ML-KEM-768 provides level 3, and ML-KEM-1024 provides level 5. As the security strength increases from 512 to 1024, the performance of the system decreases. The standard was established following a competitive process hosted by NIST. It provides different levels of protection depending on the chosen parameter set.

Transitioning to post-quantum standards involves trade-offs. When using liboqs for chat encryption, substituting the non-quantum-safe Curve25519 for ML-KEM resulted in a runtime increase of roughly 2.3 times. This shift also results in an estimated 2.3-fold increase in energy consumption and roughly 70 times more data overhead. While ML-KEM offers advantages in runtime and ciphertext size compared to other post-quantum methods, its internal hashing operations—often using Keccak variants like SHA-3 or SHAKE—account for much of its runtime, suggesting that hardware acceleration could be highly beneficial. The underlying security relies on the computational difficulty of solving specific mathematical problems. Such processes often require significant memory, though optimized versions can function with only 4 kilobytes.

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