A Study on Scalar Multiplication Parallel Processing for X25519 Decryption of 5G Core Network SIDF Function for mMTC IoT Environment

Abstract

When 5G telecommunication becomes a standardized and widely used communication medium, it must be implemented in coherence with certain 5G network standards and requirements. One such requirement is a Subscription Concealed Identifier called SUCI. SUCI prevents the exposure of international mobile subscriber identity (IMSI), which was a vulnerability in previous generation mobile telecommunication networks. Unlike IMSI, SUCI is encrypted and transmitted using a symmetric key cryptographic algorithm, to prevent the aforementioned vulnerabilities. However, for the first terminal to be encrypted, it is necessary to exchange a key with the home network, and this key exchange for SUCI encryption is performed through the Elliptic Curve Integrated Encryption Scheme (ECIES) key exchange algorithm, which is a public-key encryption scheme. However, ECIES uses more computing resources compared to a symmetric key cryptographic algorithm. Additionally, for 5G Subscriber Identity Deconcealing Function (SIDF) to satisfy the massive machine-type communication (mMTC) requirements of 5G, it is necessary to decrypt at least a million SUCIs within a short time. This puts a great burden on the 5G home network to provide the mMTC service for IoT. Therefore, in this paper, we propose a method of constructing 5G SIDF in an mMTC IoT environment. A key method of the proposed 5G SIDF configuration is the use of GPUs. This proposal was aimed at reducing the load in the mMTC environment by performing parallel processing of all cryptographic operations performed in the SIDF using a GPU. In particular, we focused on parallelization of public-key encryption algorithms. In addition, we also compared the method proposed in this paper through a survey of various 5G security products.