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The Potential of AI-powered Cyber-Security

In a recent blog post we outlined the 5 Biggest Challenges for Cyber-Security that we will have to deal with in 2019. So how to tackle these challenges? In this blog post we will talk about the potential of AI powered security strategies and explain their benefits.

Looking back leaves your assets exposed

The problem faced by businesses trying to fend off cyber criminals, is that there’s so much to keep an eye on every split second. What’s more, basing your defense on what’s already happened leaves you exposed to what hasn’t.

Traditional approaches to IT security depend on a mix of rules, signatures, and threat intelligence to detect and mitigate any potential threats.

The trouble here is that such a set-up is ‘past-centric’, and relies upon finding known attacks and attackers. Any southpaw attacks are unknown, and therefore difficult to defend against – particularly when your team is swamped with day-to-day alerts.

But not so with Artificial Intelligence

AI approach to security

AI security solutions promise to take a different approach. First they start by constructing a baseline of what ‘normal’ looks like. Once this is done, the algorithms get to work looking for abnormal events and use the results to detect attacks in real-time.

It’s a developing field, where the products currently available on the market can be divided into 2 broad categories:

  • Unsupervised learning algorithms that are left free to roam a digital network, constantly monitoring assets and the communications between them.
  • Supervised algorithms used to detect threats they’ve been trained against (an example here being malware that’s mutated from an earlier incarnation).

Extend your AI-reach to SAM

AI can also benefit your Software Asset Management (SAM), which fits into the wider security narrative. They’re both concerned with the same assets, ensuring the right upgrades are applied, and identifying the risk of unauthorized licenses.

Security and SAM share a common purpose too: define a preferred state, and identify, measure, and address any changes. AI can take SAM to a whole new level by learning from trending information. We’re already seeing Machine Learning be used to automate the processes for discovery – and then mapping associations, dependencies, and utilization. There’s also predictive analytics, which allows the technology to forecast future licensing requirements with greater accuracy.

Unleash your own SAM-moves

Unlocking a set of more advanced asset management capabilities is pure disruption. Indeed, it will challenge the very concept of what an IT asset really is, and how the security and optimization of an IT environment involves more than just what’s owned, but also what assets are:

  • leased or contracted into the business and allowed network access.
  • subscribed by users outside of IT to gain access to apps and services.
  • owned by users but utilized by the business to support operations.

Two benefits at a time

AI clearly offers a powerful new story for both IT security and SAM professionals. Where businesses can scale their digital capabilities with technology that’s faster, always on, and recognizes patterns.

All of which is helping CIOs reassess how they manage and secure assets both inside and outside the datacenter – driven by an enhanced ability to identify, associate, recognize, and interpret accurately both usage and intent.

The result: the ability to frame individual assets in the context of their role in the operational ecosystem, and their relationship to other assets, apps and services.

From this position securing an environment and keeping it compliant becomes a whole lot easier.

Leipzig, 02 / 05 / 2019

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