Machine learning in cybersecurity – an overview

ANYONE with even a passing involvement with cybersecurity – a junior helpdesk staff and upwards – will be aware that the most susceptible points of failure in any network are the carbon-based entities operating computerized technology. And even the most battle-hardened cybersecurity officer will, at some stage of their life, have at least begun to click on a link found in an email of dubious provenance. BYOD and the increased digital fluency of every organization's users have increased the pressure on security teams, as users spend longer online, on more devices, doing more complex tasks, and interacting more with others on the LAN and the internet. Endpoint security, therefore, is increasingly important. Traditional systems to protect endpoints largely work on the basis of signature detection, and methods inherited from their firewall cousins, such as black & whitelists and databases of known exploits.