Abstract
As edge computing attains tremendous popularity, IoT devices always outsource their data to nearby edge servers for storing and pre-processing, which improves the efficiency of data processing and reduces the required network resources. For privacy-preserving, sensitive data is mostly encrypted before outsourcing. Nevertheless, large volumes of data in edge computing usually comes from multiple data sources, which means that they are encrypted with different secret keys, making it difficult for edge server to query and process. Existing solutions are mostly proposed for this problem in cloud computing, but they do not take into account that the limitations of computing and storage capabilities of edge devices will prevent them from performing computationally expensive operations. In this paper, we propose a lightweight privacy-preserving equality query scheme (LPEQ) in edge computing for the first time, which allows authorized users to perform equality query efficiently and privately on the encrypted data outsourced by multiple IoT devices. We also introduce a formal security model and prove that the LPEQ meets secure requirements against curious entities under this model. Meanwhile, our theoretical analyses and experimental evaluations demonstrate that the LPEQ performs better efficiency in terms of computation and communication while retaining privacy-preserving properties. Therefore, it is practical for applications in edge computing.
Highlights
With the development of Internet of Things, large number of sensor devices explosively grow, such as smart phones, wearable devices, smart homes, etc
1) Aiming at the efficient and secure query problem for multi-source encrypted data in edge computing, we propose a lightweight privacy privacy-preserving equality query scheme, namely lightweight privacy-preserving equality query scheme (LPEQ), in which the authorized users can perform privacy-preserving equality query on the encrypted data outsourced by multiple IoT Devices in edge computing
3) We provide theoretical analyses and conduct experimental evaluations compared with other previous schemes, the results demonstrate that our scheme performs better efficiency in computation and communication while retaining privacy-preserving properties, is practical for applications in edge computing
Summary
With the development of Internet of Things, large number of sensor devices explosively grow, such as smart phones, wearable devices, smart homes, etc. 1) Aiming at the efficient and secure query problem for multi-source encrypted data in edge computing, we propose a lightweight privacy privacy-preserving equality query scheme, namely LPEQ, in which the authorized users can perform privacy-preserving equality query on the encrypted data outsourced by multiple IoT Devices in edge computing. Gen 1λ → (pk, sk): it takes the security parameter λ as input, gets an elliptic curve E(Fq) with a point P of prime order n by running G 1λ , randomly selects an integer s ← Zq and computes Q := [s] P It outputs public key pk = (E, q, P, Q) and private key sk = s.
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