Arctera InfoScale Uses AI to Detect and Stop Ransomware
▼ Summary
– Arctera InfoScale now uses AI to detect ransomware attacks in real time by analyzing behavioral patterns across applications, storage, and infrastructure.
– The system automatically triggers responses to contain attacks and prevent downtime when it recognizes ransomware traits.
– AI features include real-time data behavior analysis, adaptive learning to reduce false positives, context-rich alerts, and application-aware recovery actions.
– Full-stack monitoring provides comprehensive visibility, addressing limitations of backup-centric or single-vendor detection methods.
– This integrated approach creates a closed-loop cyber resilience system that detects threats quickly and initiates recovery to minimize impact.
Arctera has introduced advanced artificial intelligence capabilities within its InfoScale platform, empowering businesses to identify and neutralize ransomware threats in real time. This enhancement allows the system to analyze behavioral patterns across applications, storage, and infrastructure, instantly detecting the hallmarks of a ransomware intrusion as it unfolds. Upon recognition, the platform automatically initiates protective measures to limit damage and prevent operational disruption.
Bhooshan Thakar, General Manager and Vice President of Data Resilience at Arctera, highlighted the limitations of traditional security approaches. “Many organizations rely on anomaly detection that focuses narrowly on protection data, which means an attack may only be discovered after a backup finishes. Even when primary environments are monitored, restricting observation to storage infrastructure or a single vendor’s systems provides an incomplete view. A misleading sense of safety can be more harmful than having no ransomware detection plan whatsoever.”
He further explained, “Arctera InfoScale monitors the entire technology stack continuously, pinpointing ransomware activity precisely where it inflicts harm. It then enables administrators to take immediate action, curbing the attack’s impact and avoiding downtime. This strengthened resilience extends to every application across the ecosystem, regardless of deployment location.”
Key AI-driven features now available include:
Real-time data behavior analysis, which identifies attacks as they happen by tracking live data-access patterns across diverse workloads and settings.
Adaptive AI learning that constantly updates behavior baselines to enhance detection precision and lower the rate of false alarms.
Context-rich alerts linking irregularities to particular applications, storage volumes, or clusters, allowing teams to swiftly pinpoint and examine potential problems.
Application-aware actions that activate predefined recovery policies tailored to specific applications whenever an anomaly is confirmed.
Christophe Bertrand, Principal Analyst at theCube Research, commented on the broader implications. “Our recent studies on cyber resiliency and AI reveal major obstacles for organizations safeguarding essential data. While full-stack visibility and application awareness are seen as vital to recovery strategies, numerous enterprises still depend on backup-focused detection. AI-enabled solutions that offer deeper operational insight, such as spotting, isolating, and recovering from data irregularities before they compromise availability or integrity, represent a major leap in reducing ransomware and cyber-risk consequences.”
These new detection tools are fully integrated with Arctera InfoScale’s core data resiliency, high-availability, and disaster recovery functions. Together, they form a comprehensive cyber resilience framework that not only identifies dangers but also activates countermeasures to contain and remediate incidents.
Thakar emphasized the critical importance of timely detection. “Learning about a ransomware attack a week later through anomaly detection is useless, the damage is already done. With AI-powered anomaly detection in Arctera InfoScale, suspicious activity can be spotted within seconds of data being written to primary applications. This speed is invaluable, allowing teams to intervene before backup-based detection would ever trigger, thereby halting ransomware propagation, data theft, and widespread system failures.”
(Source: HelpNet Security)