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Methodology for statistical analysis of enterprise network data is becoming more important in cyber-security. The volume and velocity of enterprise network data sources puts a premium on streaming analytics - procedures that pass over the data once, while handling temporal variation in the process. In this paper we sketch SCAD: a procedure for streaming anomaly detection in the correlation between...
Network data is ubiquitous in cyber-security applications. Accurately modelling such data allows discovery of anomalous edges, subgraphs or paths, and is key to many signature-free cyber-security analytics. We present a recurring property of graphs originating from cyber-security applications, often considered a ‘corner case’ in the main literature on network data analysis, that greatly affects the...
Monitoring computer network traffic is a pressing problem in cyber-security. Such traffic can be represented as a data stream, an unending sequence of data points subject to unknown dynamics. This paper is concerned with statistical anomaly detection on such streams, where the detector must operate continuously without supervision. In this so-called continuous monitoring context, we develop a change...
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