Episode 77 of Cybersecurity Business with Fexingo dives into graph-based threat detection, which maps relationships between users, devices, and data to spot attacks that traditional rules miss. Lucas and Luna examine how this approach caught a sophisticated supply-chain compromise at a healthcare firm in Q2 2026, where attackers used stolen credentials that wouldn't have triggered alerts in a standard SIEM. The episode explores how graph databases like Neo4j are being adopted by security teams, the role of entity resolution, and why this technique is especially effective against living-off-the-land and lateral-movement attacks. Lucas also covers the challenges: scaling graph queries for real-time detection and the shortage of analysts trained in graph theory. A practical look at how one security operations center cut mean time to detect by 68% using graph-based analytics.
#GraphBasedSecurity #ThreatDetection #Cybersecurity #Neo4j #SIEM #EntityResolution #SupplyChainAttack #HealthcareSecurity #LateralMovement #LivingOffTheLand #SecurityOperations #ThreatIntelligence #DataScience #GraphTheory #Business #Technology #FexingoBusiness #BusinessPodcast
Keep every episode free: buymeacoffee.com/fexingo
