Multi-sensor network tracking research utilizing searchable encryption algorithm in the cloud computing environment

Xiaoling Sun; Shanshan Li

doi:10.7717/peerj-cs.1433

Multi-sensor network tracking research utilizing searchable encryption algorithm in the cloud computing environment

PeerJ Comput Sci. 2023 Jun 20:9:e1433. doi: 10.7717/peerj-cs.1433. eCollection 2023.

Authors

Xiaoling Sun¹, Shanshan Li¹

Affiliation

¹ School of Information Engineering, Institute of Disaster Prevention, Langfang, Hebei, China.

Abstract

Presently, the focus of target detection is shifting towards the integration of information acquired from multiple sensors. When faced with a vast amount of data from various sensors, ensuring data security during transmission and storage in the cloud becomes a primary concern. Data files can be encrypted and stored in the cloud. When using data, the required data files can be returned through ciphertext retrieval, and then searchable encryption technology can be developed. However, the existing searchable encryption algorithms mainly ignore the data explosion problem in a cloud computing environment. The issue of authorised access under cloud computing has yet to be solved uniformly, resulting in a waste of computing power by data users when processing more and more data. Furthermore, to save computing resources, ECS (encrypted cloud storage) may only return a fragment of results in response to a search query, lacking a practical and universal verification mechanism. Therefore, this article proposes a lightweight, fine-grained searchable encryption scheme tailored to the cloud edge computing environment. We generate ciphertext and search trap gates for terminal devices based on bilinear pairs and introduce access policies to restrict ciphertext search permissions, which improves the efficiency of ciphertext generation and retrieval. This scheme allows for encryption and trapdoor calculation generation on auxiliary terminal devices, with complex calculations carried out on edge devices. The resulting method ensures secure data access, fast search in multi-sensor network tracking, and accelerates computing speed while maintaining data security. Ultimately, experimental comparisons and analyses demonstrate that the proposed method improves data retrieval efficiency by approximately 62%, reduces the storage overhead of the public key, ciphertext index, and verifiable searchable ciphertext by half, and effectively mitigates delays in data transmission and computation processes.

Keywords: Cloud computing; Edge computing; Networking tracking; Searchable encryption algorithm; Verifiability.

Grants and funding

We received funding from the Fundamental Research Funds for the Central Universities (ZY20215152). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.