Provides valuable threat intelligence by collecting unstructured data
from multiple sources, storing it in big data, and performing multi-dimensional analysis using an AI-based engine.
Provides valuable threat intelligence by collecting unstructured data
from multiple sources, storing it in big data, and performing multi-dimensional analysis using an AI-based engine.
The increasing sophistication of ransomware, APT (Advanced Persistent Threats), zero-day vulnerabilities, and similar new types of attacks necessitate the integration of threat intelligence into cybersecurity strategies. Existing passive responses based on fragmented data and information appear to be insufficient, leaving a significant portion of unknown threats and abnormal behaviors undetected, with a portion of threat events likely to be false positives.
Applying threat intelligence here will help upgrade cybersecurity strategies, reduce false positives, and expand effective detection to over 90%.
Collected unstructured data will be analyzed and processed based on AI/ML and big data through multiple analysis modules (MAD, MUD, UCC, MLT, DMP).
Collected unstructured data will be analyzed and processed based on AI/ML and big data through multiple analysis modules (MAD, MUD, UCC, MLT, DMP).
Unstructured data collected from various sources through MIF, AIC, FIC modules is analyzed and processed through a continuous, iterative process consisting of Collection > Analysis > Processing > Distribution stages. Core modules within the Analyzing stage are supported by the power of AI/ML, and data is stored in BigData.
Refined threat information will be sent to MONITORAPP’s products, services, and other third-party platforms like MISP, CTAS, and Virustotal. Through this, MONITORAPP security products will be updated with real-time threat intelligence, increasing the security performance provided to enterprises.
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