Blockchain-driven machine learning-enabled intrusion-resilient authenticated key agreement protocol for edge-centric IoT systems
Vijay Karnatak, Neha Tripathi, Mohammad Wazid, Saksham Mittal, Ashok Kumar Das, Vivekananda Bhat K · 2026
Read Blockchain-driven machine learning-enabled intrusion-resilient authenticated key agreement protocol for edge-centric IoT systems by Vijay Karnatak, Neha Tripathi, Mohammad Wazid, Saksham Mittal, Ashok Kumar Das, Vivekananda Bhat K (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13389038.txt.
Description
Vijay Karnatak's team proposes BMAS-EIoT, a security scheme for edge-based Internet of Things systems, where devices process data near their source to cut delay. Such systems serve smart cities, health care, factories, and farms, but their spread-out devices face many attack routes and need both trusted device ID and break-in spotting.
The design joins blockchain-backed authentication and key agreement with machine-learning break-in spotting. The authors found it resisting a range of attacks in security analysis while beating rival schemes on speed. A working build tested the key parts, including the blockchain and spotting modules, though rollout at full scale remains unproven.
Catalog record
| CREATOR | Vijay Karnatak, Neha Tripathi, Mohammad Wazid, Saksham Mittal, Ashok Kumar Das, Vivekananda Bhat K |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 56 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |