Monitoring Temporal Homogeneity in Attributed Network Streams

Network modeling and analysis has become a fundamental tool for studying various complex systems. This paper proposes an extension of statistical monitoring to network streams, which is crucial for effective decision-making in various applications. To this end, a model for the probability of edge existence as a function of vertex attributes is constructed and a likelihood method is developed to monitor the underlying network model. The method is flexible to detect any form of anomaly that arises from different network edge-formation mechanisms. Experiments on simulated and real network streams depict the properties and benefits of the method compared with existing methods in the literature.