Updating your devices with the latest reactive or predictive security features goes some way to protecting your networks. But AI can take that further – using analytics and automation to identify new security events and instantly resolve them.
Conventional approaches to cybersecurity have relied on either reactive or predictive measures. Perimeter defences such as these aim to identify what did go wrong or what could go wrong.
Today, these still have an important role to play in protecting networks from attack. However, they’re limited in their ability to guard against innovative threats, zero-day exploits, rogue insiders and committed communities of cybercriminals.
Most importantly, when relying on conventional security measures: the more data that a business collects, the more difficult it becomes to protect. This is because the data creates a broader surface that’s vulnerable to attack.
Prescriptive security works by breaking down the siloes that were previously associated with specific security tools and making use of massive data analytic abilities, artificial intelligence and machine learning to identify potential threats more quickly than ever.
Unlike the older security models, prescriptive security relies on having large amounts of data. The more it has to protect, the faster it learns and the more effective it becomes.
This new model of security also makes use of the vast amount of data that’s held outside of an individual network – corresponding with other machines to keep track of developing threats and to understand the legitimacy of traffic. The AI is smart enough to consider: why would this device be making these particular requests?
Whereas, previously, identifying a cyber-attack might be compared to finding a needle in a haystack; we can now form a detailed picture of every stalk of hay that belongs in the stack. Modern data regulations have imposed a greater degree of order on the world of data, which makes it much easier to see when something doesn’t belong.
Handing more responsibility to prescriptive security measures can widen your network’s detection surface, decrease the reaction time and increase the velocity of response. AI will be able to either intervene autonomously or to alert human cybersecurity professionals and help them deal with threats in real-time.
Not only does prescriptive cybersecurity offer a more robust protective framework, it gives the experts more time to focus on identifying potential exploits and teaching the machines new rules for identifying and responding to attacks. This is a particularly valuable outcome considering the massive skills shortage within the industry.
Running devices on Windows 10 gives users the option to choose between different levels of prescriptive security configurations. These are designed to accommodate the most common device-use scenarios today. Microsoft Defender ATP also provides a context-aware secure score and makes prioritised suggestions for which other programs might be used to supplement security.
It’s inevitable that as computing technology continues to evolve, cyberthreats will become more complex. And there’ll be more data to protect. By 2025 it’s estimated that 463 million terabytes of data will be created every day and that the total amount of data in the world will have reached 175 billion terabytes. Prescriptive security solutions will turn that burden into an advantage. The more data you store, the safer it will become.
