Reinforcement Learning Framework Enhances Multi-Cloud Workflow Security
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🔗 Reinforcement Learning Enhances Security in Multi-Cloud Workflows. A new framework utilizing Reinforcement Learning (RL) has been proposed to improve security measures for cloud-based workflows, particularly those handling sensitive data. This innovative approach introduces adaptation chains—sequences of tailored actions that respond to security violations by considering attack characteristics and workflow dependencies. Unlike traditional methods, these chains offer a comprehensive strategy that balances conflicting objectives and reduces adaptation costs by learning from past incidents. Evaluations using jBPM and Cloudsim Plus show that this RL-driven method significantly outperforms single adaptation strategies, providing greater resilience and adaptability against security threats in multi-cloud environments.
