"Big data can improve the analyst's abilty to deal with the more human intellignce tasks, and not have to do a lot of the optimisation and statistical work that machines can do."
Large firms are likely to generate terabytes of data each day which can be monitored for the anomalous behaviour that may indicate malicious activity. This can be external and internal information, such as monitoring user profiles to identify changes in location, device used to access the network, or visits to high risk domains which are flagged up to security analysts, who can then make decision whether to take further action.
Sifting through these large volumes of information at speed is not possible for for humans, but by using big data analytics tools to process risk in real-time business can react more quickly, which is vital if there is any chance of stopping an attack in progress.
"If you look at search engine data science — for example, how does Google find a needle in the haystack in 0.1 seconds — the difference is in our world is that the search results are actually acting against us: they don't want to be found," said Cohen.
"The cat and mouse game we are playing is going to call for better data science, and so we have to be able to detect these anomalies much faster, and that means better use of big data."
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