Deep learning-based user authentication with hybrid encryption for secured blockchain-aided data storage and optimal task offloading in mobile edge computing

• Published in: Wireless networks Vol. 31; no. 3; pp. 2389 - 2417
• Main Authors: Ganesh, N. S. Gowri, Balasubramanian, V., Prasad, D. Venkata Vara, Velan, S. Senthil
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2025; Springer Nature B.V
• Subjects: Algorithms; Authentication; Blockchain; Cloud computing; Communications Engineering; Computation offloading; Computer Communication Networks; Cryptography; Cybersecurity; Data encryption; Data replication; Data storage; Data transmission; Deep learning; Edge computing; Electrical Engineering; Encryption; Engineering; Information storage; Internet of Things; IT in Business; Mobile computing; Network latency; Network security; Networks; Nuclear reactions; Optimization; Original Paper; Parameters; Privacy; Real time; Resource utilization; Secured data storage and optimal task offloading; Hybrid attribute-based encryption with the elliptical curve cryptography; Improved nuclear reaction optimization; Adaptive multiscale dilated bidirectional long short term memory; Mobile edge computing

Mobile Edge Computing (MEC) integrates edge technologies and provides consumers with low-latency storage and efficient computing services. MEC is an approach that delivers services from the cloud at the network edge and is rapidly evolving. Internet of Things (IoT) devices can run their applications...