journal article·2022Open access

Multi-dimensional Security Range Query for Industrial IoT

Abdallah Abdallah, Ayman A. Aly, Bassem F. Felemban, Imran Khan, Ki-Il Kim

Computers, Materials & Continua· Volume 72· Issue 1

Abstract

The Internet of Things (IoT) has allowed for significant advancements in applications not only in the home, business, and environment, but also in factory automation. Industrial Internet of Things (IIoT) brings all of the benefits of the IoT to industrial contexts, allowing for a wide range of applications ranging from remote sensing and actuation to decentralization and autonomy. The expansion of the IoT has been set by serious security threats and obstacles, and one of the most pressing security concerns is the secure exchange of IoT data and fine-grained access control. A privacy-preserving multi-dimensional secure query technique for fog-enhanced IIoT was proposed in light of the fact that most existing range query schemes for fog-enhanced IoT cannot provide both multi-dimensional query and privacy protection. The query matrix was then decomposed using auxiliary vectors, and the auxiliary vector was then processed using BGN homomorphic encryption to create a query trapdoor. Finally, the query trapdoor may be matched to its sensor data using the homomorphic computation used by an IoT device terminal. With the application of particular auxiliary vectors, the spatial complexity might be efficiently decreased. The homomorphic encryption property might ensure the security of sensor data and safeguard the privacy of the user's inquiry mode. The results of the experiments reveal that the computing and communication expenses are modest.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: IoT and Edge/Fog Computing · Privacy-Preserving Technologies in Data · Cryptography and Data Security

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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