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How Machine Learning and AI Helps You Stay Ahead of Cyber Threats

Published On: September 15, 2022|By |
How machine learning and AI can help you stay ahead of cyber threats

Cyber security threats continue to be a major concern for enterprise organisations everywhere – and they are growing more frequent and complex in nature. With hundreds of millions of new strains of malware emerging each year, IT departments devote significant resources to keeping their people and infrastructure protected.

In 2018 alone, there were 10.5 billion malware attacks. Increasingly intelligent and sophisticated, many of this new breed of malicious threats are able to hide from traditional anti-virus software – or even carry out their attack on systems without using any files at all in the process. Instead, they focus on entire networks or applications, and so are therefore far harder to detect.

What’s more, insider attacks from employees themselves are on the rise. As most activity mirrors that of legitimate users and is carried out on familiar devices like mobile phones and IoT infrastructure, they are also difficult to spot.

All of this means that technology solutions, tools and techniques around security have to constantly innovate and evolve just to keep pace. This is hugely challenging and puts great strain on hard-working IT admins.

However, help is at hand.

ML, AI and SIEM: your arsenal against threats

Machine learning (ML) has emerged at the very cutting edge of technology to protect organisations from these dangerous cyber threats. Using algorithms created from existing data, coupled with advanced predictive and statistical analysis, ML makes qualified assumptions about a device’s behaviour and actions – and then assesses how best to respond, based on that knowledge.

ML algorithms save security teams valuable time by identifying and analysing incidents and threats, providing visibility, accuracy and even a recommendation for action that simply isn’t possible by humans. To achieve this, these algorithms typically perform one of three mathematical tasks:

Regression: identifying correlations between different datasets, then understanding how and to what degree they are related to each other.

Classification: ‘training’ to recognise certain behaviours based on previous observations and learnings, then applying this to new data to predict future behaviour.

Clustering: working on new data and actions, but without factoring in any previous experiences or activities.

By leveraging ML’s considerable capabilities, Artificial intelligence (AI) plays a key role in helping to detect and mitigate security threats before they impact. Critically, AI is able to process far larger data volumes, at a far faster rate than any human can. Along the way, it flags any unusual or suspicious patterns of behaviour and other anomalies for investigation.

Typically created as tools within ML itself, AI uses a cause-and-effect approach (if X happens, assume Y will be the result) to construct predictable patterns of behaviour – which it then uses to judge the actions of people and devices using an organisation’s network. In this way, it vastly improves the speed, quality and effectiveness of cyber security in responding to and thwarting threats.

Good AI is typically:

Resilient: it can identify abnormal activity and prevent manipulation, coercion or other suspicious or unacceptable behaviour

Discreet: it is responsible, trustworthy and protective with all information it has access to

Transparent and accountable: it can act for you, and make educated and impactful decisions

To make the most of ML and AI, forward-thinking organisations are also now configuring a dedicated Security Information and Event Management (SIEM) solution within their operations. In essence, a SIEM gathers all available security-related data and events in one place, then correlates and analyses it with the purpose of improving responses to incidents and threats.

Stop attacks in their tracks

ML, AI and a SIEM are therefore vital building blocks for effective cybersecurity – and can make all the difference in mitigating network threats, automating application security, monitoring email activity and providing robust, next-generation anti-virus protection.

Microsoft’s security suite gives you the tools and intelligence you need to stay protected, efficiently and effectively – with less hassle for your IT team. You can enjoy the combined benefits of an advanced solution including:

Microsoft Sentinel

A scalable, cloud-native solution that provides SIEM, while managing and automating security tasks for swift response – together with accurate analytics and proactive threat intelligence – across all your users, devices, applications, and infrastructure, on-premises and in the cloud.

Microsoft Defender

Comprehensive prevention against security breaches, which manages detection, prevention, investigation, and response across all your endpoints, identities, email, and applications. As a result, your IT admins can understand and learn from threats, their likely impact and how to mitigate them going forward.

Microsoft SIEM and XDR

A dedicated solution to stop breaches across your organisation by securing its various clouds and platforms while using integrated security tools to enable a rapid response to mitigate threats.

Darktrace

A Microsoft partner and complementary tool for Microsoft’s suite which uses ML and AI to monitor user behaviour, highlight any suspicious or unusual activity and monitor it for potential risk.

There is plenty of evidence for their success.

Back in 2018, advanced cyber criminals used trojan malware to try and install

malicious cryptocurrency miners on hundreds of thousands of computers across the world. Enter Microsoft Windows Defender, which used multiple layers of machine learning to identify and block perceived threats. The crypto miners were stopped before they could do any damage – in fact, almost as soon as they started.

Meanwhile, French insurance and financial services company AXA IT puts its trust in Darktrace cyber security to identify and manage online threats. Here, machine learning is used to scan for network vulnerabilities and automate responses.

However, success depends not only on installing on the stand-alone technical solutions – but also on ensuring they are properly configured to deliver the best results.

How we can help

Our security team are experts in securing and maintaining modern work environments with best practice and best-in-class solutions. Our Managed Security Service brings together the combined power of Microsoft’s offerings to mitigate threats while removing the hassle of maintaining a secure environment at work through our monitoring, management and updates. Meanwhile, our Threat & Vulnerability Assessment gives you an accurate picture of the security of your environment and specific areas for improvement.

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