Why AI and machine learning are vital cybersecurity tools for 2022
Matt Aldridge, Principal Solutions Consultant at Carbonite + Webroot, explores how understanding of AI/ML is lagging behind
Cybersecurity threats are evolving at an alarming pace. There’s nothing new about that – cybercriminals are always seeking new ways to compromise business systems, so as soon as one threat is identified and neutralised, we should already be on the lookout for the next.
COVID-19 has, if anything, only accelerated this evolution thanks to the vulnerabilities presented by rapid digital transformation and the transition to remote working – coupled with uncertainty that bad actors have been only too happy to exploit.
It goes without saying that IT teams need to be properly equipped to deal with these threats, but alarmingly, there is evidence that many IT decision-makers do not feel that they are properly set up for this mammoth task. A recent AI/ML report from Carbonite + Webroot revealed that both enterprise organisations and SMBs (small- and medium-sized businesses) believe they’ve been harder hit by cyber attacks in the last year than in those before. However, just 19% of enterprise IT decision-makers say their current tools help stop all their cyber security-related threats, down from 36% in the company’s previous annual survey.
Fortunately, artificial intelligence and machine learning (AI/ML) technologies can deliver the powerful new cyber security tools ITDMs crave, and offer hope in our ability to keep up with the latest cyber threats. While adoption of AI/ML technologies has been increasing, understanding of how they work and the true benefits they offer is trailing behind.
The power of AI/ML
From data analysis to customer service and much more, the applications of AI/ML for IT departments are ever increasing. Cyber security is no exception to this, and these new technologies are helping to boost automation and identify emerging threats before they can wreak havoc with your systems.
Thanks to hybrid working models, businesses’ attack surfaces are larger than ever; it’s not possible to even conceive of manually identifying and monitoring all devices in your networks and the possible vectors available to cyber criminals. Fortunately, AI/ML is a powerful tool for increasing the automation and efficiency of your security systems. These technologies can rapidly analyse millions of events across your network to locate the threats that could harm your organisation.
For time-stretched security professionals, this automation is invaluable, helping them avoid getting bogged down in day-to-day minutiae so they can focus on the bigger picture. At a time when attacks and opportunistic scams are on the rise, you want to be able to focus on strategy and training your workforce to identify and avoid threats rather than worrying about monitoring and configuring your security systems.
AI and machine learning tools can help people do their jobs more effectively. This is because security professionals are always in short supply, and now possibly unavailable or distracted with other pressing concerns. Additionally, businesses are facing unprecedented demands on their networks and people, especially with new working from home concerns. So, automation technology would be welcomed as it can provide many benefits for struggling businesses.
For example, threat detection is no longer a human-scale problem – AI/ML offers a solution that allows organisations to match that scale. However, AI/ML offers much more than just automation. As a subset of AI, machine learning involves self-learning algorithms that progressively improve their performance by training themselves on data sets.
In the case of security, by analysing millions of events, AI/ML technologies learn to identify deviations from established norms. Instead of countering the latest threats after they have been identified like traditional systems do, AI/ML can identify anomalies as they emerge. Against the background of quickly evolving threats, it’s not hard to see how valuable this is for protecting against data breaches and maintaining uptime and business continuity.
Despite these many benefits – and evidence of significant adoption by businesses – proper understanding of AI/ML-enabled security continues to lag.
93% of respondents to Carbonite + Webroot’s survey from enterprises (organisations with 1,000 employees or more) claimed to use cyber security tools with AI/ML, but it is clear that many ITDMs do not fully understand their benefits. 55% said that, although their tools claim to use AI/ML, they weren’t sure what that means.
Meanwhile, SMBs with far more limited resources are unlikely to have dedicated security experts to help protect them, and may be underestimating the threats they face. The survey found that while nearly half of SMBs reported having had their data stolen or breached at least once, an equal number claimed their data had never been exposed – which is extremely unlikely considering both cyber crime statistics and the boom in attacks since the COVID pandemic began.
Education is vitally important to ensure that organisations of all sizes know that they are receiving the full protection offered by AI/ML technologies – and that these are properly configured and utilised by IT teams and end users to maximise their effectiveness. For SMBs with limited resources, this will also help to ensure that they are getting the most out of their budgets and that they are not unknowingly allowing cyber criminals to access their networks.
Well-established security experts like Carbonite + Webroot can help in this, offering the most up-to-date AI/ML technologies and building security systems based on your needs. It’s important to trust your security partner – to know that they will be honest with you and take their responsibilities seriously, and that they will offer the training and support you need to make sure that everyone in your organisation is working to maintain your security.
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