TL-ABKS: Traceable and lightweight attribute-based keyword search in edge–cloud assisted IoT environment
Edge–cloud coordination offers the chance to mitigate the enormous storage and processing load brought on by a massive increase in traffic at the network’s edge. Though this paradigm has benefits on a large scale, outsourcing the sensitive data from the smart devices deployed in an Internet of Things (IoT) application may lead to privacy leakage. With an attribute-based keyword search (ABKS), the search over ciphertext can be achieved; this reduces the risk of sensitive data explosion. However, ABKS has several issues, like huge computational overhead to perform multi-keyword searches and tracing malicious users. To address these issues and enhance the performance of ABKS, we propose a novel traceable and lightweight attribute-based keyword search technique in an Edge–cloud-assisted IoT, named TL-ABKS, using edge–cloud coordination. With TL-ABKS, it is possible to do effective multi-keyword searches and implement fine-grained access control. Further, TL-ABKS outsources the encryption and decryption computation to edge nodes to enable its usage to resource-limited IoT smart devices. In addition, TL-ABKS achieves tracing user identity who misuse their secret keys. TL-ABKS is secure against modified secret keys, chosen plaintext, and chosen keyword attacks. By comparing the proposed TL-ABKS with the current state-of-the-art schemes, and conducting a theoretical and experimental evaluation of its performance and credibility, TL-ABKS is efficient.
Authors
- Ashok Kumar Das (ORCID: https://orcid.org/0000-0002-5196-9589)
- M. Shamim Hossain (ORCID: https://orcid.org/0000-0001-5906-9422)
- Joel J. P. C. Rodrigues (ORCID: https://orcid.org/0000-0001-8657-3800)
- Uma Sankararao Varri (ORCID: https://orcid.org/0000-0003-0875-6606)
- Youngho Park (ORCID: https://orcid.org/0000-0002-0406-6547)
- Debjani Mallick (ORCID: https://orcid.org/0009-0002-7413-7854)
Publication Details
- Journal
- Alexandria Engineering Journal
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1016/j.aej.2024.09.030
- Citations
- 6
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.94
Funders
- King Saud University