Open AccessIPO-PEKS: Effective Inner Product Outsourcing Public Key Searchable Encryption from Lattice in the IoT
Author(s) -
Miao Wang,
Liwang Sun,
Zhenfu Cao,
Xiaolei Dong
Publication year - 2024
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2024.3368908
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Lightweight devices in the Internet of Things (IoT) typically need to store massive data on a cloud server with strong processing and storage capabilities for later retrieval and usage. Since these data contain the participant’s sensitive information, they cannot be delivered directly to the cloud server. Public-key Encryption with Keyword Search (PEKS) allows customers to search for target encrypted files using keywords. However, the majority of PEKS implementations are unable to repel malicious quantum-capable attackers. And with regard to forward security, they must search for many rounds to obtain the necessary data. To resolve these concerns, we propose a comprehensive Inner Product Outsourcing PEKS system (IPO-PEKS) with forward security based on LWE assumptions, which raises search efficiency by allowing authorized clients to find the information they desire in a single round and achieves more fine-grained searches. Furthermore, we offer an inner product outsourcing calculation technique that allows the server to compute the inner product result without knowing the details of both parties in order to conceal the relevant privacy data of transmitting and decryption states. The paradigm can be utilized for efficient state transition through the use of parallel computing to accomplish the target of one round of iteration.