Is it time for AIOps to take its place at the heart of cybersecurity measures?
Modern hybrid IT environments generate a staggering volume of data – and with that comes an equally overwhelming flood of security alerts.
Some of these are legitimate business-critical warnings; unfortunately, many others are not. Those false positives or low-priority notifications bury the signals that truly matter, meaning the real problems that need addressing are often missed by overstretched IT teams.
This ‘needle in a haystack’ dilemma – coupled with the inevitable alert fatigue – is a perfect storm for cyber attackers, who are counting on finding weaknesses and oversights in an organization’s network. Something needs to be done to sharpen digital defenses on a systematic level. AIOps (AI for Operations) can lead the way in delivering that protection.
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The cost of false alerts
You only need to go through your email’s junk folder to see unwanted noise. Likewise, in business, IT security teams are often forced to sift through thousands of alerts every day, many of which require no action at all. In fact, one study conducted by Cybsafe discovered that ‘more than half of today’s office workers are ignoring important cybersecurity warnings due to overwhelm and fatigue from digital communication’.
It’s natural to become complacent when confronted by constant misinformation, but when the system cries wolf too often, real threats can sneak through the cracks. High false positive alert rates distract cybersecurity professionals from the matter at hand, despite every second mattering during a digital assault or data breach. One missed red flag can quickly escalate into a genuine crisis, leading to reputational damage, operational downtime, and regulatory scrutiny.
Finding clarity with AIOps
By integrating machine learning and advanced analytics across large datasets, AIOps can empower organizations to ignore all that noise and focus on the alerts that actually need attention. These platforms are trained to detect the anomalous behaviors and patterns that indicate a potential threat – whether that’s uncharacteristic login activity, unusual spikes in user traffic, or unanticipated system changes.
Why is this so important? Because, as it stands, there are simply too many data sources and network access points for teams to simultaneously observe on their own, which means the level of end-to-end visibility granted by AIOps is now needed more than ever. Similarly, it’s unproductive for IT teams to be going around in circles in pursuit of a threat that they can’t predict or locate.
Thankfully, AIOps can flag threats in real-time and, in some cases, even resolve the issue without IT teams needing to step in. For instance, a global Financial Services company recently used auto-remediation software to reduce major incident counts by ‘150-200 per month’, underscoring the value of this technology in improving key cybersecurity metrics.
Building scalable cyber resilience
As a business expands, so does its attack surface. So, unless an organization is willing to risk human fatigue and excessive man-hour costs to manually surveil its security perimeters as it grows, it will require constant intelligent automation to keep those progressively sophisticated threats at bay.
The good news is, AIOps platforms are built to scale with complexity, adapting to new environments, users, and risks as they develop. And organizations can feel reassured that their digital vulnerabilities are safeguarded for the long term.
For example, modern methods of attack, such as hyperjacking, can be identified and mitigated with AIOps. This form of attack in cloud security is where a threat actor gains control of the hypervisor – the software that manages virtual machines on a physical server. It allows them to then take over the virtual machines running on that hypervisor.
What makes hyperjacking especially dangerous is that it operates beneath the guest operating systems, effectively evading traditional monitoring tools that rely on visibility within the virtual machines. As a result, systems lacking deep observability are the most vulnerable. This makes the advanced observability capabilities of AIOps essential for detecting and responding to such stealthy threats.
Naturally, this evolving scope of digital malice also requires compliance rules to be frequently reviewed. When correctly configured, AIOps can support organizations by interpreting the latest guidelines and swiftly identifying the data deviations that would otherwise incur penalties.
Once free from the burden of handling false alerts and constantly reassessing their strategy, skilled IT professionals can return their focus to higher-priority initiatives aimed at business growth. When coupled with the enhanced data-driven and real-time decision-making that only AI can provide, this streamlined performance will considerably reduce operational business costs, too.
Getting ahead of cyber threats, today and tomorrow
With the threat landscape continuously evolving, organizations need a security model that adapts just as quickly. Caught under a cloud of overwhelming data and false security alerts, IT teams are lacking the time and resources to conduct their operations with conviction, accuracy, and productivity. It’s time for AIOps to take its place at the heart of cybersecurity postures.
By turning guesswork into certainty and reaction into anticipation, these platforms offer a scalable way to enhance visibility, reduce alert fatigue, and ultimately enable security teams to get ahead. With the power of AIOps, organizations can seamlessly shift towards a digital defense they can rely on – where agility, foresight, and security all take center stage.
