Research Article
Exploiting Machine Learning to Detect Malicious Nodes in Intelligent Sensor-Based Systems Using Blockchain
Table 2
Feature comparison with respect to proposed model.
| Contributions | Ref. No. | Similarities | Differences | Limitations |
| Registration and authentication | [8] | Distributed network authentication | Hybrid blockchain different levels of nodes registered at different platforms | Complex to manage two blockchains | [30] | Authentication | Use of multiblockchains and cluster manager | Difficult to manage |
| Routing | [7] | Routing, MN detection | Calculate through Qlearning | Consumes more energy while discovering the route | [14] | Distributed network, routing | Localization-based routing | Select relatively longer path, which causes rapid energy |
| MN detection | [10] | Distributed network, registration, MN detection | Detection through network parameters, calculation of node’s reputation | Uses computationally complex consensus algorithm | [29] | Detection through ML, distributed network | SDN-based network, multilevel detection | Considered very few attacks |
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