The age of automation begins for security operation centers

Security operations centers (SOCs) face lower productivity and increased security threats caused by a lack of visibility into complex environments, an inability to analyze cloud-scale volumes of data, and difficulties in improving team performance.

Ineffective SOCs are providing an opening for cybercriminals in today's rapidly changing threat landscape, which has seen a surge in the volume of sophisticated attacks. More than half of these firms said they believe upcoming cyberattacks would be a catastrophe for their organization. According to research by Illumio, 75% of organizations acknowledged at least one ransomware incident in the past year.

An inefficient SOC puts pressure on analysts, leading to even greater burnout for cybersecurity specialists. Systems used by organizations are left open to potentially crippling attacks like data breaches, which could irreparably harm a company's status both financially and publicly. Modern businesses must transform their SOCs to embrace autonomy to cut through the clutter and concentrate on the risks that matter most.

Traditional SOC operations cause burnout

Cyber attackers have improved in sophistication and originality during the last decade. The response from the cyberspace sector has been the development of more tools and platforms to identify intrusions or malicious behavior. Increased cyber activity, especially during the hybrid work trend, resulted in an explosion of data that SOCs could not handle adequately.

Security teams collect data from various sources, including applications, IoT devices, mobile devices, transactions, and the resident cloud environment, to gain visibility into the entire attack surface. But even then, the constantly shifting surface makes it challenging to view the entire picture.

This is when autonomy comes into play. Contrary to outdated beliefs, autonomy does not imply the complete eradication of humans. An autonomous SOC can use artificial intelligence (AI) and data science to continuously learn from events, allowing it to develop as conditions change and holistically comprehend the complete attack story. It gives analysts additional insights and enhancements and provides them with a practical strategy.

The autonomous SOC collects all essential information about an attack when suspicious activity is noticed and creates the context analysts need to identify, isolate, and neutralize the assault without wasting time on pointless warnings swiftly and effectively. It results from the deluge of information currently overwhelming analysts and gives the notifications greater meaning and value. Because the intelligent system has already reviewed them, security personnel will treat those notifications more seriously and be able to respond to them confidently.

It is impossible to emphasize the effect this will have on employee bandwidth. Devo's SOC Performance Report indicates that 71% of security professionals are considering leaving their jobs due to a variety of SOC issues, including burnout brought on by an increase in workload and information overload, a scarcity of downtime, a lack of tool integration, and alert fatigue. Most SOC employees—78%—work overtime, putting in an extra seven hours per week on average.

Employees can think more critically and creatively about the attack patterns they observe when liberated from repetitious, boring chores. They are given more time to focus on an alert without being continually distracted.

How to automate security operations centers

Traditional SOCs cannot keep up with the technological arsenal that cybercriminals have. Many legacy technologies are outdated and lack the sophisticated analytics required to utilize the volume of data being ingested fully. New government restrictions are also raising concerns about compliance. Chief information security officers and other leaders are battling for every dollar of their SOC budget due to a bleak economic outlook. The SOC Performance Report's poll of cybersecurity leaders found that 25% have budgetary pain points.

SOCs must add more potent AI and machine learning (ML)-based automation to the existing security stack to expand on it and give analysts a complete picture of threats throughout the organization's infrastructure more effectively and efficiently. These components offer SOC analysts a path to follow. Ingestion, correlation, analysis, conceptualization, prioritization, action, resolution, auditing, and learning are all capabilities that a perfect autonomous SOC will possess.

Scalable data gathering and extensive analytics should be available through a single dataset without silos or data replication in an autonomous SOC that delivers on supplementing the analyst to increase the SOC's effectiveness. Attack-tracing AI should be used to conduct autonomous alert investigations and threat hunting, alleviating most of the workload on SOC analysts. The platform either takes action to remediate the attack or notifies an analyst to act and give feedback to the AI after a thorough, evidence-based narrative of a detected assault is built out. This collaboration enables the autonomous SOC to learn and improve continuously.

A security team's day-to-day workforce is prepared to accept an autonomous SOC. In Devo's survey, 37% of respondents who were asked how organizations can enhance the SOC mentioned ML, advanced analytics, and automation. According to IDC, 30% of major business organizations will switch to autonomous security operations centers by 2026, which scattered teams may access for quicker incident management, remediation, and response.

To streamline operations and support the frequently overworked and underappreciated security teams who work hard to preserve a company's data and the viability of its business, leaders should pay attention to their workers and turn to the autonomous SOC.