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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...
How can we effectively use costly statistical models in the defence of large computer networks? Statistical modelling and machine learning are potentially powerful ways to detect threats as they do not require a human level understanding of the attack. However, they are rarely applied in practice as the computational cost of deploying all but the most simple algorithms can become implausibly large...
The normal-mesh-based image coder of Jansen, Baraniuk, and Lavu (JBL) is studied. First, the JBL coder is introduced, and several of its shortcomings are identified. Then, to address these shortcomings, three modifications to this coder are proposed, namely, the use of a data-dependent base mesh, an integer representation for normal/vertical offsets, and a different scan-conversion scheme based on...
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