Microsoft Copilot for Security - Threat Intelligence Use Cases - Part 2

March 25, 2024 | 3 min read

Micah Heaton

Executive Director, Managed Security Center of Excellence

Micah Heaton Square Calcite Duotone

In the previous three blog posts in this series, we covered how AI and Microsoft Copilot for Security can assist various security teams with tasks such as threat hunting, compliance alignment, and finding zero-day vulnerabilities. This blog serves as a part two to our previous blog on Microsoft Copilot for Security - Threat Intelligence Use Cases.

In this blog, our AI experts focus on network security. We will explore different use cases where Microsoft Copilot for Security can augment Azure Firewall security capabilities. We will discuss how network security teams can use AI to gain insights into network use patterns and assist in identifying anomalies that could be indicators of malicious activity.

Augment Azure Firewall with Microsoft Copilot for Security

Azure Firewall provides network security capabilities, including network traffic filtering and monitoring. While it offers some insights into anomaly detection and network pattern monitoring, using AI will significantly enhance those insights, including:

  • Anomaly Detection – Train AI to recognize normal behavior based on historical data and flag any deviations as potential security threats
  • Behavioral Analysis – Review the behavior of network users and applications. Identify abnormal patterns such as suspicious user activity, unusual application behavior, or unauthorized access attempts
  • Traffic Classification – Categorize network traffic based on protocols, applications, and user activities. Flag any activity that deviates from normal or expected use
  • Threat Intelligence Integration – Integrate threat intelligence feeds with Azure Firewall and leverage Copilot to analyze and correlate threat data to network activity in real-time
  • Security Optimization Recommendations – Analyze and recommend firewall rules to close unnecessary ports or block malicious or noisy traffic
  • Review Logs – Analyze logs and firewall rule configurations to identify misconfigurations, compliance violations, or security policy gaps
  • Leverage Sentinel – Identify network logs with high-security value and integrate them with Sentinel
  • Continuous Learning – Copilot learns from new data to ensure that network behavior and pattern analytics remain fresh, are effective, and will dynamically adjust to changing network conditions

By combining Copilot for Security with Azure Firewall, organizations can gain deeper insights into network patterns, identify anomalies, and improve overall network performance and efficiency. Additionally, by leveraging Azure's ecosystem, like Microsoft Sentinel, network logs can be correlated with other security logs to identify subtle threats that may otherwise be bypassed.

Gain More Security Insights from Your Network with Microsoft Copilot for Security

Detecting anomalies in network traffic is a crucial task in maintaining the security and integrity of an organization’s IT infrastructure. Microsoft Copilot for Security can efficiently analyze vast amounts of network data and identify suspicious activities, such as:

  • Complex Pattern Recognition – Capture complex patterns and relationships in large-scale datasets to detect subtle deviations from normal behavior
  • Adaptability – Use new data quicker and adapt faster to changing network environments and evolving attack techniques
  • Automation – Operate autonomously, continuously monitoring network traffic and alerting administrators when anomalies are detected
  • Scalability – Scale to analyze large volumes of network traffic in real-time
  • Detection of Unknown Threats – Identify previously unseen or zero-day attacks by detecting deviations from normal network behavior
  • Reduced False Positives – Accurately distinguish between benign anomalies and genuine security threats
  • Comprehensive Analysis – Analyze and view multiple dimensions of network traffic simultaneously, including packet headers, payload content, protocol behavior, and temporal patterns
  • Early Detection – Detect unusual patterns in network traffic faster, enabling organizations to respond quicker to security incidents

Leveraging AI and Copilot for Security for network pattern analysis and anomaly detection enhances the effectiveness, efficiency, and responsiveness of cyber defenses. It helps organizations discover bad actors who are conducting malicious activities across their infrastructure faster.

BlueVoyant is an early adaptor and member of Microsoft’s Design Advisory Council for Copilot for Security. Further, BlueVoyant was recognized by the Microsoft Intelligent Security Association (MISA) as the Security MSSP (Managed Security Service Provider) of the Year. Our commitment to our clients is to continually provide guidance on how and where to optimize security operations with Microsoft, including Copilot for Security.