Simulation of distributed denial of service attack against ethereum smart contract on the blockchain

Abstract

The perception and functional infrastructure of smart networks are changing as a result of the advent of blockchain technology and the proliferation of IoT-driven devices. Deploying Ethereum's smart contracts, the blockchain allows secure administration, authentication, and access to IoT equipment. Blockchain-IoT systems are creating a high amount of sensitive data due to increased demand and growth. DDoS assaults pose the most serious danger to smart contracts in blockchain-IoT systems, according to a new report. Smart contracts in blockchain-IoT systems currently lack any kind of security mechanism. Artificial intelligence approaches for threat categorization utilizing Adaptive Weighted MLP ("Multi-Layer Perceptron") are used first in the proposed security architecture to provide complete autonomy in making decisions. The primary job of the transaction handling engine is to use adaptive weighted MLP to categorize transactions into regular and attack kinds. If the transaction is legitimate, the smart contract will carry out its business logic and add it to the blockchain network in the cloud, where it will be included to future transactions. SHA-256 hash value calculation is used to generate the certificate key. Ethereum Blockchain-based proof of authority is used for data aggregation and transaction addition in the Consensus blockchain mechanism. Homomorphic cryptography schemes are also applied to enhance security. To avoid intrusions, the security of the system is improved. The proposed framework's performance is measured against a real-world IoT dataset, called BoT-IoT20,21, which comprises current DoS ("Denial-of-Service"), DDoS (Distributed Denial-of-Service Attack"), and other IoT-based attack samples. We used a variety of assessment measures to determine how effective the suggested distributed system is in finding DDoS attacks. It's also been likened to some of the most modern approaches in the field.