Author Identifier

Muhammad Waqas: https://orcid.org/0000-0003-0814-7544

Document Type

Journal Article

Publication Title

Sensors

Volume

24

Issue

23

PubMed ID

39686134

Publisher

MDPI

School

School of Engineering

RAS ID

76656

Funders

Major Science and Technology Projects in Yunnan Province (202202AD080013) / National Key Research and Development Project of China (2019YFB2102303) / National Natural Science Foundation of China (61971014) / King Khalid University (RGP.2/373/45)

Comments

Peng, T., Gong, B., Tu, S., Namoun, A., Alshmrany, S., Waqas, M., ... & Chen, S. (2024). Forward and backward private searchable encryption for cloud-assisted industrial IoT. Sensors, 24(23). https://doi.org/10.3390/s24237597

Abstract

In the cloud-assisted industrial Internet of Things (IIoT), since the cloud server is not always trusted, the leakage of data privacy becomes a critical problem. Dynamic symmetric searchable encryption (DSSE) allows for the secure retrieval of outsourced data stored on cloud servers while ensuring data privacy. Forward privacy and backward privacy are necessary security requirements for DSSE. However, most existing schemes either trade the server’s large storage overhead for forward privacy or trade efficiency/overhead for weak backward privacy. These schemes cannot fully meet the security requirements of cloud-assisted IIoT systems. We propose a fast and firmly secure SSE scheme called Veruna to address these limitations. To this end, we design a new state chain structure, which can not only ensure forward privacy with less storage overhead of the server but also achieve strong backward privacy with only a few cryptographic operations in the server. Security analysis proves that our scheme possesses forward privacy and Type-II backward privacy. Compared with many state-of-the-art schemes, our scheme has an advantage in search and update performance. The high efficiency and robust security make Veruna an ideal scheme for deployment in cloud-assisted IIoT systems.

DOI

10.3390/s24237597

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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