Listening to what the system tells us: Innovative auditing for distributed systems - Di Pilla, Piergiuseppe; Pareschi, Remo; Salzano, Francesco; Zappone, Federico (Frontiers in Computer Science, 2023)
Software ecosystems have become increasingly large and complex in recent times and more distributed, as evidenced by the growing diffusion of blockchains and distributed ledgers. Effective management of this complexity requires constant monitoring of the system’s health, capturing signals that may indicate malfunctions, anomalies, vulnerabilities, and attacks in progress. Using log auditing effectively meets the requirement of stringent system health monitoring for traditional systems. However, it is not apparent how to transfer these methodologies to distributed contexts characterized by exponentially higher levels of complexity. Instead, it is a question of defining innovative methods that consider the nature of distributed systems to grasp the diversity of signals that may arise with maximum flexibility. To this end, we describe an architecture for system auditing capable of coping with this complexity by exploiting the potential offered by advanced data analytics, natural language processing, and artificial intelligence to grasp “what the system tells us.” We subsequently illustrate an implementation of this architecture as given by the DELTA (for Distributed Elastic Log Text Analyzer) auditing tool and describe its application to Hyperledger Fabric, the most widespread and successful platform for implementing private blockchains.