Somewhat Homomorphic Encryption: Ring Learning with Error Algorithm for Faster Encryption of IoT Sensor Signal-Based Edge Devices

Abstract

In recent years, Homomorphic Encryption (HE) has shown the possibility of securely running a computation arbitrarily without performing the data decryption. Many authors have shown Somewhat Homomorphic Encryption (SHE) or Fully Homomorphic Encryption (FHE) schemes implemented practically on both the addition and multiplication operations for SHE. The recent methods for implementing the FHE methods completely depend on arbitrarily reducing the time taken to perform the encrypted multiplication operation to increase the computation power required by SHE methods. This paper aims to accelerate the encryption primitives in an integer-based SHE based on the duration between each data transmission from the sensor and data packaging method. If the number of sensors increases exponentially in an edge device environment, the signals have to be encrypted faster in a packed mode in the edge environment and transferred to the cloud without a loss in data. The presented SHE method reduces the time taken for encryption based on the input number from the sensor and invariably increases the performance of the edge device. This advantage also helps the deploying healthcare application obtain end-to-end privacy in transmitting sensitive patient data.