It’s no secret that organizations are struggling to keep up with the ever-changing methods of cybercriminals and the growing volume of attacks.
In 2021 alone, cyber-attacks are said to have increased 50% year over year. Meanwhile, further research suggests that a company falls victim to the attempts of threat actors every 39 seconds as 30,000 websites are hacked every day, while almost two-thirds (64%) of organizations have experienced at least one form of cyber-attack.
Such statistics highlight the huge opportunities for attackers. As they see success in the deployment of modern attack methods, they continue to deploy them at scale, hoping to reap lucrative rewards.
The unfortunate outcome of this for cybersecurity professionals is unprecedented pressure – a situation exacerbated by the industry’s growing capability deficit. Indeed, it is estimated that the number of unfilled cybersecurity positions grew from one million to 3.5 million between 2013 and 2021.
Between a shortage of security professionals and a rampant attack landscape, the balance is firmly tilted in favor of threat actors who are free to conduct malicious activities at will. At the same time, organizations scramble to protect their systems, forever playing catch up.
Yet the situation isn’t necessarily a lost cause. Thankfully, technologies are beginning to show more significant promise in turning the tide in favor of security professionals.
From machine learning and artificial intelligence (AI) to robotic process automation (RPA), we’re now seeing the potential role of those cutting-edge innovations, from providing real-time insights to even predicting when and where attacks might happen.
Cyber strategies can no longer rely on a process of detection and remediation. Today, a more proactive outlook is required – something that these advanced solutions can achieve the difference between security professionals being in the dark and having full transparency in critical moments.
When it comes to cybersecurity, visibility and knowledge are everything. It allows security professionals to dramatically reduce the time taken to detect and deal with a threat, helping to react at speed to ransomware attacks and save significant sums induced by downtime.
This is the gap that these technologies can help to bridge.
Why do companies need to generate data lakes?
As is typically the way with technology, the theory is often easier than the real-world application.
The solutions we are discussing here are not a case of plug-and-play. Their effectiveness is reliant upon the ability of their users to cultivate the necessary environment in which they can thrive.
Here I’m talking about the need for data – data that is both reliable and available in high volumes.
Given the current threat landscape, security decision-making simply must be data-driven. Without data, machine learning models, for example, will fail to obtain the required understanding of a specific operating environment’s inner workings and, by default, fail to take accurately informed actions.
Fortunately, data is abundant.
In 2021 alone, 79 zettabyte were created, captured, copied, and consumed worldwide (one zettabyte equating to one trillion gigabytes). Companies should work to find ways in which they can expand their datasets – and ideally create a data lake – even if this is solely for the purpose of security.
Only then can they start to unlock the true potential of game-changing technologies as weapons in the fight against cybercrime.
With accurate data lakes powering machine learning security solutions, cybersecurity teams will be able to take a quantum leap with their security strategies. Much of the burden of detecting and responding to anomalous activities are not only lifted from security professionals but dealt with in real-time by technologies thanks to automated responses being triggered.
2022: A year of challenges and opportunities
Many such companies are already on the path to achieving this quantum leap, successfully implementing automated detection and response tools into their strategies – something that I believe we will continue to see throughout 2022.
That said, it won’t all be plain sailing. For instance, in terms of interoperability, we’re seeing issues regarding partner technologies making this transition a little more complex than companies may have anticipated.
Meanwhile, the mass pandemic-induced shift to the cloud has left companies managing several competing priorities, which may serve to push automated detection and response down the agenda.
The fact that the perimeter no longer exists is a challenge that many organizations are still navigating, with firms working to understand what interfacing and accessing data in different ways means from a security perspective.
However, despite these added complexities, security teams still need to monitor activities and make informed logical decisions.
To deal with sophisticated threats, security responses need to be dynamic to be effective. Therefore, just as the cloud has become a critical component in improving the effectiveness of company operations, automation must equally become a vital pillar of security.
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