Authorized Block-Mining-Based Intrusion Detection System in Blockchain Enabled IOT Devices Using CDS-KA and BiLeCun-ALSTM

In the proposed framework, Corollary De-swinging K-Anonymity (CDS-KA) ensures the secure registration and privacy preservation of Internet of Things (IoT) device details, while Bidirectional LeCun Aranda Long Short-Term Memory (BiLeCun-ALSTM) works in tandem within the Intrusion Detection System (IDS) to classify and predict potential attacks. The collaboration between these components enhances both privacy and security, ensuring efficient detection and protection of sensitive data in blockchain-enabled IoT devices. The integration of blockchain technology with IoT devices brings numerous benefits, such as transparency and data integrity. However, it also raises significant privacy concerns. Yet, none of the existing works concentrates on energy-efficient authorized block mining. Hence, this paper proposes an energy-efficient-aware, Authorized Block-Mining-based IDS (ABM-IDS) in blockchain-enabled IoT devices using CDS-KA and BiLeCun-ALSTM. Primarily, the IoT devices are registered using the device details, and then the details are preserved using CDS-KA. At the time of registration, keys and smart contracts are created. The solidity code is used to generate the smart contract. Then, the Merkle tree (MT) is created from the smart contract using GXNOR-BLAKE 512. Also, the solidity functions are split, followed by hash code generation. Then, the generated hash code is updated in the MT. Similarly, the optimal blocks are recognized from the hash code and also verified in the MT. Conversely, the user logs into the network, and then data sensing is done. Thereafter, the data are encrypted and then balanced via Edward Modulo Curve Cryptography (EMCC) and SCC-AZOA, respectively. Now, the balanced data is input to the IDS. In an IDS, the steps such as data collection, pre-processing, feature extraction, feature selection and classification are done. The proposed BiLeCun-ALSTM significantly predicts whether the data is attacked or not. Afterward, the non-attacked data is sent to the destination in a secure manner by verifying the blockchain. Collectively, the proposed framework obtained better security with an accuracy of 98.65%.