Smart Agentic AI- powered scalable blockchain security for efficient traffic data sharing using deep featured ensemble learning
DOI:
https://doi.org/10.31838/NJAP/08.01.21Keywords:
Agentic Artificial Intelligence, Blockchain Security, Intelligent Transportation Systems (ITS), Traffic Data Sharing, Deep Feature Learning, Ensemble LearningAbstract
The number of communications between Road Side Units (RSUs) of Intelligent Transportation Systems (ITS) has been exhibiting a marked increase and poses tremendous threats to the reliable and secure real-time exchange of data between the units. The conventional cryptography mechanisms and conventional intrusion detection systems tend to fail with a large amount of traffic; not only do they have poor scalability and inefficient key management, but they are also vulnerable to advanced cyberattacks. To address these disadvantages, a Smart Agentic AI-enabled scalable blockchain-based security architecture is recommended in this paper. The framework has secured, smart, and efficient processing of traffic data through deep-featured ensemble learning and superior encryption processes.The architecture will have a Preprocessing and Feature Normalization step, where z-score normalization will be used to normalize the RSU traffic data. The procedure reduces the impact of the outlier points and statistical features that are skewed, and allows performing the data analysis consistently and without any bias in different traffic situations. This normalized data is then fed into the AANT-OMPEN model (Ant Colony Optimized Multi-Perceptron Ensemble Network), which is a combination of the dynamic/relevant feature selection method and an ensemble of neural networks of Multi-layer Perceptron (MLPN). Aggregated decision fusion also contributes to the improvement of the detection accuracy, which makes the performance metrics better (precision, recall, and Accuracy) as compared to traditional models.The safe transfer of the traffic data ensues a multi-layered blockchain approach once classified. This encompasses the CPH-AES (Cross Pointed Hyper Cloaking AES) algorithm that is quite resistant to key leakage and predictability of ciphertext. Tamper resistance is also enhanced by the SMLFSBCP (State Matrix Lattice Fold Shuffle Blockchain Policy). Finally, the Master Node Provable Key Authentication Policy (MNPKAP) is a zero-knowledge proof and a digital signature to verify that communication is safe between RSUs in the ITS setting.
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