Abstract:
The IoV prioritizes secure communication. Node trust affects IoV security. Therefore, before acting on a message, evaluate its trustworthiness. Malicious nodes can broadcast fake events to gain network control. False reports and malicious vehicles make emergency networks unreliable.
This study presents a unique trust framework that considers most IoV trust aspects to accurately identify malicious nodes and events. VANETs have many IoV shortcomings, but trust models have been proposed. They lack energy and practicality.
All models use static scenarios and fixed parameters. The proposed framework uses context-aware cognitive AI. The framework cognitively learns the environment from the report and contextualizes an event.
The framework detects and screens malicious nodes using anomaly outliers in addition to trust management (TM). Experimental simulations assessed framework performance. The framework was compared to industry leaders. Performance indicators rise. The trust-management framework could improve IoV security.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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