Ahead in the Clouds

Nov 17 2017   2:31PM GMT

Cloud AI in the enterprise: Making the security case

Caroline Donnelly Profile: Caroline Donnelly

Tags:
Artificial intelligence
cloud
Cloud Security

In this guest post, Ross Brewer, managing director and vice president for Europe, Middle East and Africa at cybersecurity software supplier LogRhythm, makes the enterprise case for using artificial intelligence (AI) in the fight against cybercrime.

Organisations face a growing number of increasingly complex and ever-evolving threats – and the most dangerous threats are often the hardest to uncover.

Take the insider threat or stolen credentials, for example. We’ve seen many high-profile attacks stem from the unauthorised use of legitimate user credentials, which can be extremely difficult to expose.

Organisations are under growing pressure to detect and mitigate threats like these as soon as they arise, and this is only going to increase when the much talked about General Data Protection Regulation (GDPR) comes into force on 25 May 2018.

Security teams have a critically important job here. They need to be able to protect company data, often without time, money or resources on their side. This means they simply cannot afford to spend time on extensive manual threat-hunting exercises or deploying and managing multiple, disparate security products.

Cloud AI for efficiency

The perimeter-based model of yesterday is insufficient for the mammoth task of protecting a company’s assets. Instead, we are starting to see a shift towards automation and the application of cloud-based Artificial Intelligence (AI), which is fast becoming critical in the fight against modern cyber threats.

In fact, a recent IDC report predicted that the AI software market would grow at a CAGR of over 39% by 2021, whilst separate research from the analyst firm stated that the future of AI requires the cloud as a foundation, with enterprise ‘cloud-first’ strategies becoming more prevalent over the same period.

The cloud is, without doubt, transforming security by enabling easy and rapid customer adoption, saving time and money, and providing companies with access to a class of AI-enabled analytics that are not otherwise technically practical or affordable to deploy on-premise.

Plug-and-play implementation lets security teams focus on their mission instead of spending valuable time implementing and maintaining a new tool.

What’s more, when deployed in the cloud, AI can benefit from collective intelligence and a broader perspective to maximise it. Imagine incorporating real-world insight into specific threats in real-time. This will advance the ability of AI-powered analytics to detect even the stealthiest or previously unknown threats more quickly, and with greater accuracy than ever before.

Using cloud AI to detect unseen threats

By combining a wide array of behavioural models to characterise shifts in how users interact with the IT environment, cloud-based AI technology is helping organisations pursue user-based threats, including signatureless and hidden threats.

Applying cloud-based AI throughout the threat lifecycle will automate and enhance entire categories of work, as well as enable increasingly faster and more effective detection of real threats. Take analytics, for example. Hackers are constantly evolving their tactics and techniques to evade existing protective and defensive measures, targeting new and existing vulnerabilities and unleashing attack methods that have never been seen before.

Cloud AI is beginning to play an important role in detecting these emerging threats. The technology is proactive and predictive, without the need for security and IT personnel to configure and tune systems, automatically learning what is normal and evolving to register even the most subtle changes in events and behaviour models that suggest a breach might be occurring.

Cloud-based AI essentially helps security analysts cut through the noise and detect serious threats earlier in their lifecycle so that they can immediately be neutralised. It provides rapid time-to-value through cloud delivery, and promises to eliminate or augment a considerable number of time-consuming manual threat detection and response exercises. This allows security teams to drive greater efficiency by focusing on the higher-value activities that require direct human touch.

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