Incident Management | Breaking Cybersecurity News | The Hacker News

The current SOC model relies on a scarce resource: human analysts. These professionals are expensive, in high demand, and increasingly difficult to retain. Their work is not only highly technical and high-risk, but also soul-crushingly repetitive, dealing with a constant flood of alerts and incidents. As a result, SOC analysts often leave in search of better pay, the opportunity to move beyond the SOC into more rewarding roles, or simply to take much-needed breaks. This high churn rate puts the SOC in a vulnerable position, jeopardizing the overall effectiveness of cybersecurity operations. To keep your team resilient and maintain operational efficiency, it's essential to take proactive steps to reduce burnout and improve retention. Here are five strategies that can make a difference. Why Analyst Burnout Matters More Than Ever SOC analyst burnout is becoming a critical issue as the cybersecurity landscape evolves. Security Operations Centers (SOCs) face a growing number of daily al...

In the last decade, there has been a growing disconnect between front-line analysts and senior management in IT and Cybersecurity. Well-documented challenges facing modern analysts revolve around a high volume of alerts, false positives, poor visibility of technical environments, and analysts spending too much time on manual tasks. The Impact of Alert Fatigue and False Positives  Analysts are overwhelmed with alerts. The knock-on effect of this is that fatigued analysts are at risk of missing key details in incidents, and often conduct time-consuming triaging tasks manually only to end up copying and pasting a generic closing comment into a false positive alert.  It is likely that there will always be false positives. And many would argue that a false positive is better than a false negative. But for proactive actions to be made, we must move closer to the heart of an incident. That requires diving into how analysts conduct the triage and investigation process. SHQ R...

In recent years, artificial intelligence (AI) has begun revolutionizing Identity Access Management (IAM), reshaping how cybersecurity is approached in this crucial field. Leveraging AI in IAM is about tapping into its analytical capabilities to monitor access patterns and identify anomalies that could signal a potential security breach. The focus has expanded beyond merely managing human identities — now, autonomous systems, APIs, and connected devices also fall within the realm of AI-driven IAM, creating a dynamic security ecosystem that adapts and evolves in response to sophisticated cyber threats. The Role of AI and Machine Learning in IAM AI and machine learning (ML) are creating a more robust, proactive IAM system that continuously learns from the environment to enhance security. Let's explore how AI impacts key IAM components: Intelligent Monitoring and Anomaly Detection AI enables continuous monitoring of both human and non-human identities , including APIs, service acc...