Abstract
In July 2022, the National Institute of Standards and Technology (NIST) announced its selection of four algorithms for post-quantum cryptography standardization in advance. Among these algorithms, Kyber was chosen as the only key encapsulation mechanism (KEM). In the Kyber KEM, the modular reduction function is utilized in numerous areas. We have discovered that by modeling controllable modular reduction functions, unknown modular reduction functions can be targeted. And attacks can then be constructed. Henceforth, profiling can be mounted on the target device. In this paper, we present a machine-learning-based key recovery attack on Kyber, without needing a reference device. We have effectively attacked the modular reduction function. Furthermore, this vulnerability that enables the reuse of the same function could be utilized in other attacks.