AI Case Study: AI for Insider Threat Detection at Exabeam
Exabeam, a leading cybersecurity company, is revolutionizing insider threat detection through User and Entity Behavior Analytics (UEBA) and Machine Learning.
By analyzing user behavior and identifying anomalies, Exabeam helps organizations detect insider threats before they escalate, leading to a 92% reduction in insider-related security incidents and a 45% improvement in security response times.
Read Top 15 Real-Life Use Cases For AI In the Cybersecurity Industry.
Background
Insider threats pose a significant risk to organizations, leading to:
- Data breaches expose sensitive business information.
- Financial losses resulting from fraud or intellectual property theft.
- Reputation damage, eroding customer trust and business credibility.
Traditional security systems struggle with:
- Detecting subtle insider threats, as attackers often use legitimate credentials.
- High false positives, overwhelming security teams with alerts.
- Slow response times, allowing threats to persist undetected.
To address these challenges, Exabeam’s AI-driven approach:
- Analyzes user activity across IT environments to establish behavioral baselines.
- Uses machine learning to detect deviations that could signal malicious intent.
- Provides risk-based alerts to prioritize real threats and reduce noise.
How Exabeam Uses AI for Insider Threat Detection
1. AI-Powered User Behavior Analytics (UBA)
📌 How It Works:
- AI models analyze login attempts, file access patterns, and network activity to establish normal behavior.
- Anomalous behavior triggers alerts, such as unauthorized file downloads or unusual login locations.
- Machine learning adapts to evolving threats, improving detection accuracy.
🔹 Example: A multinational corporation detected an employee attempting to exfiltrate trade secrets, preventing a potential $10 million intellectual property theft.
Read an AI case study about Artemis and IoT.
2. Risk-Based Threat Scoring & Prioritization
📌 How It Works:
- AI assigns risk scores to user activities based on historical behavior and threat intelligence.
- High-risk users are flagged for further investigation, reducing false positives.
- Security teams receive prioritized alerts, improving response times.
🔹 Example: An enterprise using Exabeam reduced false positive alerts by 60%, allowing security analysts to focus on genuine threats.
3. Automated Threat Response & Incident Investigation
📌 How It Works:
- AI correlates data from multiple security tools to provide a unified threat timeline.
- Automated investigation workflows streamline threat resolution.
- AI-driven playbooks recommend mitigation steps to security teams.
🔹 Example: A financial institution cut its insider threat response time by 45%, preventing potential regulatory violations and compliance breaches.
Read an AI case study from Cisco about Stealthwatch.
Benefits of AI-Powered Insider Threat Detection at Exabeam
✅ 92% Reduction in Insider Threat Incidents – AI detects threats before they escalate.
✅ 45% Faster Response Times – Automated workflows improve threat mitigation.
✅ 60% Fewer False Positives – AI reduces security alert fatigue.
✅ Enhanced Regulatory Compliance – AI helps organizations meet data protection standards.
✅ Stronger Data Protection – Prevents unauthorized access and data exfiltration.
The Impact of AI on Exabeam’s Insider Threat Strategy
By leveraging AI, Exabeam has transformed insider threat detection:
- Stronger security posture, reducing data leaks and financial losses.
- Faster incident response, minimizing damage from insider threats.
- Improved security team efficiency, allowing focus on high-risk events.
- Better compliance management, ensuring adherence to regulatory requirements.
Conclusion
Exabeam’s AI-driven insider threat detection is redefining cybersecurity. Using UEBA and Machine Learning, the platform detects and mitigates insider risks more effectively than traditional solutions.
With a 92% reduction in insider-related incidents, 45% faster response times, and 60% fewer false positives, Exabeam’s AI-powered approach is setting new standards in corporate security. As insider threats evolve, AI-driven behavior analytics will play an even greater role in protecting organizational data and assets.
