{"id":68055,"date":"2023-10-23T11:04:31","date_gmt":"2023-10-23T10:04:31","guid":{"rendered":"https:\/\/www.microsoft.com\/en-gb\/industry\/blog\/?p=68055"},"modified":"2023-10-23T11:04:34","modified_gmt":"2023-10-23T10:04:34","slug":"cyber-defence-in-the-age-of-ai","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-gb\/industry\/blog\/cross-industry\/2023\/10\/23\/cyber-defence-in-the-age-of-ai\/","title":{"rendered":"Cyber defence in the age of AI"},"content":{"rendered":"\n

In this age of digital disruption, as every business strives to become hyper-connected, cybercrime becomes ever more impactful and disruptive to our economy and our society, with far-reaching effects on individuals and businesses. Defenders are fighting an asymmetrical battle, where attackers are often better skilled, resourced, and organised than many security teams. Nor do attackers have to play by the same rules we must. Compounding this, in most organisations, the incident response team can receive far more security alerts than they can realistically manage.<\/p>\n\n\n\n

The use of automated detection and response systems can help tip the scale in favour of defenders by using risk-based algorithms and anomalous activity detection to flag events that require human expertise to investigate further. This helps security analysts detect patterns and behaviours that are not obvious to the human eye, with more precision and speed than human defenders alone.<\/p>\n\n\n\n

The background to “cognitive cyber”<\/h3>\n\n\n\n

As advances in dynamic and adaptive cyber defence systems become reality, what do organisations need to do to become ready for cognitive cyber, and what exactly is it? <\/p>\n\n\n\n

Cognition refers to the mental processes involved in gaining knowledge and comprehension. Cognitive cyber attempts to simulate that process with the application of self-learning algorithms, natural language processing,<\/ins> and big-data mining techniques as applied to the cybersecurity domain. It uses cognitive system overlays to traditional artificial intelligence (AI)\/machine learning (ML) models to achieve something greater than the sum of the parts. <\/p>\n\n\n\n

To recap:<\/p>\n\n\n\n