Hillstone AI-Driven Security Solution

Digital transformation has led to information and data increasing at explosive rates, and as a result, data and network security can no longer be performed with traditional threat detection and prevention techniques, whether manual or automated.

In addition, today’s Advanced Persistent Threat (APT) attacks usually involve a targeted, sophisticated and multi-stage process, known as the cyberattack kill chain. A typical APT involves multiple phases using different behavior and the attack tools, which are constantly modified to avoid static or signature-based detection.

Because of all these dynamics, security and IT teams are turning to AI and ML technologies to address threat defense battles that otherwise would be impossible by human or manual processes alone.

Statistics Source: Varonis /blog/cybersecurity-statistics

Hillstone’s AI and ML technologies work effectively across the entire attack detection, analysis and response phases. These techniques monitor behaviors along the attack path, then build models for standard profiles or baselines of behavior for users and other entities. Anomalous activity is flagged as suspicious, and security admins are alerted for further analysis. The AI engines also automatically ingest other forensic information from sources, such as threat intelligence and reputation, to reduce noise and enhance accuracy.

Traffic analysis is another area where Hillstone’s AI-driven security shines. Given that the volume of network traffic is massive, it is impossible for a human alone to conduct real-time monitoring and analytics. AI or ML-based techniques can help establish normal traffic baselines, with comprehensive visibility, and abnormal or suspicious behavior can be identified, analyzed, and alerted.