Enhanced Blockchain-Based Data Poisoning Defense Mechanism

Abstract

This paper deals with a new secured execution environment which adapts blockchain technology to defend artificial intelligence (AI) models against data poisoning (DP) attacks. The Blockchain Governance Game (BGG) is a theoretical framework for analyzing the network to provide the decision-making moment for taking preliminary cybersecurity actions before DP attacks. This innovative method for conventional decentralized network securities is adapted into a DP defense for AI models in this paper. The core components in the DP defense network, including the Predictor and the BGG engine, are fully implemented. This research concerns the first blockchain-based DP defense mechanism which establishes an innovative framework for DP defense based on the BGG. The simulation in the paper demonstrates realistic DP attack situations targeting AI models. This new controller is newly designed to provide sufficient cybersecurity performance measures even with minimal data collection and limited computing power. Additionally, this research will be helpful for those considering using blockchain to implement a DP defense mechanism.

Keywords

• machine learning
• Blockchain Governance Game
• data poisoning attack
• convolutional neural network
• mixed game
• cybersecurity