As technology advances, so does the threat landscape, with cyber criminals effectively exploiting weak points on an almost daily basis. When malware infiltrates an organisation’s first layer of defence, it can spread quickly throughout the network, exposing data and weakening security - and in most cases this happens faster than analysts or administrators have time to react to. Indeed, with reams of data being generated and transferred over networks, organisations are having a hard time monitoring everything, which means potential threats can easily go unnoticed.
Organisations need to rely on machines to detect and respond to threats more quickly and efficiently. Even enterprises with a dedicated security team that monitors the latest security threat trends and understands the blueprint of evolving attack vectors still need to continuously monitor all network activity. The sheer volume of processes, services and applications running on a corporate network is just too much for human beings to monitor alone. However, this doesn’t mean that human analysis is not important.
User and entity behavioural analytics (UEBA) is essential in keeping up with continuously evolving threats and making sense of anomalous network behaviour. Security approaches that utilise both machine learning and human analysis enable all threats to be analysed for effective detection and response, ensuring all data is accounted for and including the human element to help reduce the opportunities for false positives. To keep up with the ever-changing security landscape, companies need to integrate internal and external threat context in their environment by updating processing rules for operating systems, applications, and network devices in order to strengthen the accuracy of real-time machine analytics.