Cloud security threats are evolving all the time. Find out how AI can help you monitor, detect and respond.
We're living in a golden age of cloud technology. Each year, cloud infrastructures become that bit more scalable, flexible and secure. In just a few years, the business world has gone from cloud-friendly to cloud-first.
There is, however, a sting in the tail. As cloud technologies grow in complexity, so too do threats to security.
Gone are the days when you could visualise an IT security perimeter with a pencil sketch on the back of a napkin. Gone is the "ring road" model of networking, with spokes emerging from a central hub.
No, today's networks look like what you'd get if you asked a child to draw a topographical map from memory. Lines sprawl and overlap as users and devices enter and exit the network from different locations.
Security has never been more important. At the same time, security has never been more niche. Businesses want the reassurance that their data is safe – not only to protect their staff and clients but also to avoid getting a slap on the wrist from GDPR.
The thing is that the vast majority of businesses outsource at least some of their cloud computing infrastructure to an external provider.
Sure, the Amazons and Oracles of the world have plenty of resources. They certainly appear to be investing in cutting-edge cloud security. Nevertheless, it's only reasonable to want to check, double-check and triple-check that your data and applications are secure.
How do cloud providers and cloud security solutions ensure they're covering all bases? One answer is the combined power of artificial intelligence (AI) and machine learning (ML). These innovative technologies can help with threat detection and response, task automation, data analytics and more.
Here, then, are some of the ways AI is changing and improving cloud security. But first, how has cloud security changed?
How has cloud security changed?
Cloud security has always been a game of cat and mouse with hackers. As they identify and attack novel weak spots, security solutions have to be proactive in their responses.
Traditional methods such as firewalls, encryption, MFA and IAM only go so far. Companies are still vulnerable to weak access controls, misconfigurations and even insider threats. Meanwhile, AI-generated phishing emails are bypassing traditional filters.
As cloud environments get more complex, these threats increase – and at a time when most businesses have gone all in on multi-cloud environments, this is a legitimate cause for concern.
That's the state of play. So, how can AI help? Here are six ways.
1. Threat detection and response
AI is a super-calculator, able to crunch mystifying amounts of data in seconds.
This makes it ideal for analysing network traffic and security logs. It can scan huge datasets that would require an insupportable amount of human monitoring. It can then identify and respond to threats quickly and effectively.
Threat response could involve blocking a malicious IP address, putting more monitoring in motion, or isolating an affected system.
With such a large attack surface to cover, AI can tighten the locks even further.
2. Automation
What are people good for? Some would say that staff should focus on tasks machines can't do. It's the same principle as getting a robot to build a car and a human to monitor the robot.
This is one of the key benefits of getting AI to automate cloud security operations. It means IT doesn't have to send out alerts or orchestrate a threat response. Instead, sysadmins can use their time more efficiently, focusing on tasks that need a human touch.
3. Behavioural analysis
What if the security threat is coming from inside? It's a real problem that can cause IT teams sleepless nights.
One powerful use of AI is to analyse internal user behaviour and spot any anomalies that might otherwise slip under the net.
Is there a deviation in day-to-day access patterns? Is a user transferring an unusually large amount of data? These behaviours can trigger alerts for IT to deal with – and learn from each instance to reduce the chance of false alarms.
But behavioural analysis isn't just about response. It's also about forecasting problems and anticipating changes in resource needs.
AI can predict new attack vectors – something that even the smartest security analyst will struggle to do. It can then recommend preventative measures.
AI, then, is proactive as well as reactive. It can predict, monitor, contain and neutralise threats.
4. Data analytics
Data is one of a business's greatest assets. But if it's not analysed and put to work, it's just, well, a load of words and numbers.
AI can enhance data analytics, furnishing IT and management with insights. These, in turn, can bring businesses closer to the Holy Grail of data-driven decision-making.
5. Threat neutralisation
Is that a threat on the horizon? Sometimes, threats march towards you with a sign that says "neutralise me". Other threats are more sly.
The fact is that it's becoming harder and harder to anticipate zero-day vulnerabilities – and harder and harder to spot phishing attempts.
AI is always ahead of the game. It can neutralise threats before they turn into costly, disruptive security breaches.
6. Adaptive access controls
Are your access permissions static? The answer is probably "yes" – unless you've deployed AI-driven cloud security.
Granular access permissions are essential to ensure the security of your cloud infrastructure. Think of your cloud environments as a hotel: not every guest and member of staff needs access to the same rooms.
AI takes this one step further by introducing dynamic, adaptive controls. These adjust user permissions in real time based on factors like user location, access time, and device type.
It's just one way that AI is bringing cloud security into the age of multi-cloud environments, hybrid working and large attack surfaces.
Will these technologies transform the cloud security landscape? We think so. Either way, we'll be sure to keep you in the loop about any exciting advances.
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