The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Attribute-Based Encryption With Parallel Outsourced Decryption for Edge Intelligent IoV
Abstract
Edge intelligence is an emerging concept referring to processes in which data are collected and analyzed and insights are delivered close to where the data are captured in a network using a selection of advanced intelligent technologies. As a promising solution to solve the problems of insufficient computing capacity and transmission latency, the edge intelligence-empowered Internet of Vehicles (IoV) is being widely investigated in both academia and industry. However, data sharing security in edge intelligent IoV is a challenge that should be solved with priority. Although attribute-based encryption (ABE) is capable of addressing this challenge, many time-consuming modular exponential operations and bilinear pair operations as well as serial computing cause ABE to have a slow decryption speed. Consequently, it cannot address the response time requirement of edge intelligent IoV. Given this problem, an ABE model with parallel outsourced decryption for edge intelligent IoV, called ABEM-POD, is proposed. It includes a generic parallel outsourced decryption method for ABE based on Spark and MapReduce. This method is applicable to all ABE schemes with a tree access structure and can be applied to edge intelligent IoV. Any ABE scheme based on the proposed model not only supports parallel outsourced decryption but also has the same security as the original scheme. In this paper, ABEM-POD has been applied to three representative ABE schemes, and the experiments show that the proposed ABEM-POD is efficient and easy to use. This approach can significantly improve the speed of outsourced decryption to address the response time requirement for edge intelligent IoV.
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Cited by
Liang, S., Wu, H., Zhen, L., Hua, Q., Garg, S., Kaddoum, G., Hassan, M. M., & Yu, K. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3158253 · Cited by 367
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Ramu, S. P., Boopalan, P., Pham, Q.-V., Maddikunta, P. K. R., Huynh-The, T., Alazab, M., Nguyen, T. T., & Gadekallu, T. R. (2022) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.103663 · Cited by 301
Self-citationEPPDA: An Efficient Privacy-Preserving Data Aggregation Federated Learning Scheme
Song, J., Wang, W., Gadekallu, T. R., Cao, J., & Liu, Y. (2023) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2022.3153519 · Cited by 150
Identity-Based Broadcast Proxy Re-Encryption for Flexible Data Sharing in VANETs
Zhang, J., Su, S., Zhong, H., Cui, J., & He, D. (2023) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2023.3299466 · Cited by 63
Metadata
- Authors
- Feng, C., Yu, K., Aloqaily, M., Alazab, M., Lv, Z., & Mumtaz, S.
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 2020-11
- Volume
- 69
- Issue
- 11
- Pages
- 13784-13795
- ISSN
- 0018-9545 (ISSN-L)
- 1939-9359
- OpenAlex
- W3091074232
- Cited by
- 253
- References
- 37
- FWCI
- 18.09
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Funders
- National Natural Science Foundation of China (61373163, 61902203)
- Japan Society for the Promotion of Science (JP18K18044)
- Key Research and Development Plan - Major Scientific and Technological Innovation Projects of ShanDong Province (2019JZZY020101)
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- Feng, C., Yu, K., Aloqaily, M., Alazab, M., Lv, Z., & Mumtaz, S. (2020). Attribute-Based Encryption With Parallel Outsourced Decryption for Edge Intelligent IoV. IEEE Transactions on Vehicular Technology. https://doi.org/10.1109/tvt.2020.3027568
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