Harnessing Data Provenance and Security Attribution for Resilient Cloud Systems
L. Suresh, Sangay Chedup · 2024
As cloud computing continues to play a pivotal role in modern data ecosystems, the management and security of data have become increasingly complex. This chapter provides a comprehensive exploration of data provenance and security attribution within cloud environments. It begins with an overview, defining the significance of data provenance and exploring its applications in machine learning on platforms like Google Cloud and Amazon Web Services (AWS). Emphasis is placed on the pivotal role of security attribution in safeguarding machine learning systems, demonstrated through examples like AWS CloudTrail. The chapter transitions to data provenance in machine learning, showcasing distributed workflows using Apache Atlas in the Hadoop ecosystem on Azure. Current research trends, provenance-aware machine learning algorithms, and real-time tracking in cloud-native environments are discussed. Security attribution is explored further, addressing federated learning with AWS Security Hub and emerging technologies such as blockchain-based attribution. The interplay between data provenance and security attribution is highlighted, with case studies illustrating tools like Azure Purview for unified data governance and security. Leveraging provenance data for improved security attribution, including predictive models, is explored with practical case studies. Future directions predict an integration of artificial intelligence (AI) and machine learning in advanced provenance systems, addressing privacy concerns, and anticipating technological advancements. Challenges encompass ethical considerations, scalability issues, and user acceptance challenges. Recommendations for practitioners include best practices for implementing data provenance and security attribution, emphasizing the use of cloud-specific tools like Azure Monitor and AWS CloudTrail for comprehensive cloud security. This chapter serves as a comprehensive guide for navigating the intricate landscape of data provenance and security attribution in cloud computing.