Elevating threat detection and response to a new level – IT Security Guru

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Cybersecurity platforms have emerged as indispensable assets for threat detection, response and management. They proactively keep tabs on network traffic, user behaviour and system activities to identify and mitigate risks before they escalate into potentially catastrophic breaches. Yet, the efficacy of these platforms varies significantly, sending SOC teams an overwhelming volume of security alerts per day.

The phenomenon commonly referred to as ‘alert fatigue’ not only compromises the effectiveness of threat detection but also strains the capacity of security teams to respond promptly and decisively to genuine threats. Dealing with thousands of alerts weekly, SOC analysts face the challenging task of distinguishing real threats from false positives. According to recent research by Deep Instinct, a staggering 45% of all alerts turn out to be false positives. The time they spend grappling with security alerts frequently surpasses the hours they have in a day, leaving them overwhelmed and stretched thin. Fortunately, solving SOC alert fatigue without adding to headcount is possible.

Adopting a multifaceted approach to solving alert fatigue 

Addressing the alert fatigue challenge requires a multifaceted approach, incorporating technological advancements and strategic initiatives aimed at streamlining alert management processes and enhancing the efficacy of threat detection and response.

One critical strategy involves normalising log data into a single format. In traditional SOCs, data is sourced from a multitude of tools and platforms, each generating disparate data points. By consolidating data into a unified format, organisations can improve data quality and provide analysts with comprehensive visibility into suspicious behaviour across the network, enabling more effective threat mitigation.

Additionally, modelling typical user and device behaviour is essential for reducing alert fatigue. Rather than relying solely on rule-based alerts, integrating user and entity behaviour analytics (UEBA) allows SOCs to establish baseline behaviour patterns and flag deviations that may indicate potential threats. Continuous adaptation to changes in the organisation’s environment enhances the accuracy of threat detection while minimising falsely triggered alerts.

Finally, organisations can benefit from automating data correlation and MITRE ATT&CK mapping to further enhance SOC efficiency. Advanced correlation capabilities automatically analyse security observations and contextualise them with data from multiple sources to identify genuine threats. This approach streamlines the investigation process, enabling SOC analysts to prioritise and respond to incidents more effectively.

Boosting efficiency with AI 

According to the latest study by SenseOn, 83% of SOC teams said they would benefit from tools that use AI to automate security activity. Investing in AI-based solutions would particularly help individual SOC analysts to reduce stress associated with ongoing staff shortages and the flood of alerts they receive on a daily basis. The same study highlighted that 53% of cybersecurity professionals said they’d like to see tools implemented that would reduce the level of alerts.

This growing preference for AI-based tools highlights their importance not only in reducing the alert burden but also in strengthening the overall resilience of organisational defences against evolving cyber threats. As such, the integration of AI into cybersecurity platforms is increasingly recognised as both a strategic advantage and a vital necessity.

By leveraging AI’s advanced analytics capabilities and adaptive algorithms, cybersecurity platforms can discern genuine threats from noise, significantly reducing the incidence of false positives. This ensures that SOC analysts are presented with actionable insights that demand immediate attention, enabling them to prioritise their efforts and respond swiftly to emerging threats.

From blocking suspicious IPs to thwarting command-and-control exploits, AI empowers businesses to adopt a proactive stance against cyber threats, minimising the window of opportunity for malicious actors to exploit vulnerabilities. Its ability to take data from endpoint, network, cloud, and user telemetry and created a unified analysis enhances situational awareness.

The result of enhancing threat detection and response capabilities, cybersecurity platforms with AI capabilities offers tangible cost savings for organisations. By streamlining operations and reducing the incidence of false positives, it enables organisations to better optimise resource allocation and maximise the efficiency of their security operations. With potential savings in analyst costs and a reduction in Security Information and Event Management (SIEM) expenses, AI offers a cost-effective solution to the burgeoning cybersecurity challenges facing organisations today.

By David Atkinson, CEO, SenseOn

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