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Seceon aiSIEM

Seceon® aiSIEM goes beyond using the log data, simple analysis for correlation of events and applying rules for data analysis. The solution uses elastic compute power, dynamic threat models, user and entity behavioral analytics (UEBA), threat intelligence feeds for correlation and enrichment, advanced machine learning (ML), AI with actionable intelligence and proprietary feature engineering and anomaly detection algorithms without a need to establish rules. It includes, large-scale and robust collection and enhanced analysis of logs and data from cloud, endpoints and other IT data sources beyond rules, fast and scalable search over volumes of raw data and, most importantly, automated response to contain and eliminate the threats in real-time. Additionally, it is designed to support enterprise SOC teams and MSSPs because of its scalable and distributed architecture. It integrates with 3rd party ticketing systems and takes over operations of DR site in case of disaster. Key Features: Operations Management
  • Long Term Storage and Analysis of Raw Logs up to 7 years
  • Configurable data retention policies
  • Integrates with 3" party ticketing systems
  • Threat intelligence hub
  • Takes over operations of DR site in case of disaster
Dynamic Threat Models
  • Automate the task of writing rules in order to detect real threat issues from plethora of threat indicators
  • Threat models are based on patented technology where rules are all preconfigured and they adjust dynamically
  • Learns and improves over time while significantly reducing alert volume
Contextual Real-time Alerts with Automated Analysis & Correlation
  • No rules to define and no thresholds to adjust
  • Analyzes data and incorporates threat intelligence feeds for correlation
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The ROI4CIO Product Catalog is a database of business software, hardware, and IT services. Using filters, select IT products by category, supplier or vendor, business tasks, problems, availability of ROI calculator or price calculator. Find the right business solutions by using a neural network search based on the results of deployment products in other companies.