Practical Inner Product Encryption for Privacy-Preserved Internet-of-Things Applications

In recent years, we have witnessed a remarkable proliferation of Internet of Things (IoT) devices, which are quickly penetrating into almost every industry and making tremendous impacts on the national economy and the entire society. However, security and privacy remain a fundamental hurdle in the collection, transmission, and processing of IoT data. This work focuses on privacy-preserved data access that is critical for implementing and exploiting the full potential of future IoT. This work represents the first endeavor to develop practical Compact Inner Product Encryption (C-IPE) aiming to achieve privacy-preserved data access in IoTs. We propose a practical scheme that provides effective, fine-grained, and privacy-preserved access to IoT data while at the same time, is computationally efficient for practical deployment on resource-constrained IoT devices to preserve the designers of energy-efficient embedded systems and applications a balance between performance, power, security, and cost-effectiveness. We also analyze the efficiency of C-IPE. Compared with the original IPE, the key size is reduced from n + 1 to a small constant; the ciphertext size is reduced by half, i.e., from 2n + 2 to n + 1; and the decryption effectively avoids the high cost of cryptographic pairing. These salient properties result in high efficiency in computation and storage, making C-IPE well-suited for IoT applications. To demonstrate the practicality of our scheme, we implement C-IPE in three representative privacy-preserving applications: privacy-preserved attribute matching, distance matching, and linear regression in IoT settings. We carry out extensive experiments on four platforms, i.e., Dell workstation, Raspberry Pi 3 with an ARM Cortex processor, Samsung Galaxy 7, and ultra-low-power Arduino Nano 33 micro-controller using 32-bit ARM Cortex-M0 CPU with 256KB Flash and 16KB RAM. The experimental results demonstrate significant improvements over existing IPE schemes, supported by detailed numerical evidence and comparative figures across practical application settings.