While SIEMs are the backbone of security monitoring and triggering alerts, evolving threats demand solutions that can affordably handle large data volumes, use AI/ML for smarter threat detection, and integrate external threat intelligence. 

SIEM Data Storage is Costly, But Reducting Observable Data Increases Risk
Storing all security logs in a SIEM is expensive, leading many companies to cut costs by limiting data intake or reducing retention periods. However, this creates blind spots, making it harder to detect prolonged attacks. Solutions like data lakes offer scalable storage options that allow organizations to retain extensive data cost-effectively, enabling better long-term threat detection.

SIEMs Have Limited AI/ML Capabilities, Making Custom Algorithm Development Difficult
SIEMs primarily rely on rules-based analysis and often lack the flexibility to support custom machine learning models. This is problematic as evolving threats demand adaptive detection beyond preset rules. Using dedicated AI/ML platforms such as Databricks alongside SIEMs allows for custom models that identify unusual patterns, like increased access to sensitive data, enabling advanced threat detection.

SIEMs Often Can’t Ingest Third-Party Data, Limiting Threat Detection Insights
Effective cybersecurity relies on external intelligence, like IP threat lists and vendor data, but many SIEMs struggle to incorporate these sources. Without this integration, organizations miss valuable insights on emerging threats. Integrating third-party data into the security framework provides a complete view of potential threats, empowering teams to respond proactively.

Enter SIEM Plus Entrada Gatehouse

Entrada’s Gatehouse Security solution offers a centralized and cost-effective way to store, monitor, and enrich SIEM data, enhancing your organization’s cybersecurity capabilities. Built on the Databricks Data Intelligence Platform, Gatehouse uses proprietary graph networks and large language models (LLMs) to analyze network events and alert you to genuine threats. When a threat is detected, its event graph capabilities provide rapid insights into root cause analysis and downstream impact. The data intelligence platform provides full-spectrum support for GenAI development, making it the perfect foundation for the Entrada Gatehouse Cybersecurity Solution.

Key Features:

Reduce Storage + Compute Costs: Minimize storage and compute costs while storing more data, enabling more efficient and robust threat-hunting.
Robust AI/ML Modeling: Robust threat detection by creating custom algorithms and automation with expanded lookback periods.
Regulatory Compliance: Ensure industry and regulatory compliance needs are met with actionable data retention and lookback.
360-Degree View with Enriched Data: View your entire technology footprint plus more contextual data sources.
Geofencing – Analyze IoT device location data and user behavior patterns to automatically detect unauthorized access attempts.

With Entrada’s Gatehouse, your organization can enhance its security posture, optimize operational costs, and meet compliance needs effectively. Entrada offers full stack Databricks implementations services from Data Engineering to advanced AI capabilities, with accelerators designed for every step of Databricks adoption. Reach out to Entrada today to learn more.

About Entrada
Entrada is a Databricks-focused consulting and implementation partner backed by Databricks Ventures. Entrada harnesses the power of Databricks to help customers accelerate their AI + data initiatives. Our expertise in AI/ML, Databricks, and analytics is centered around industry-centric solutions. Our mission is to simplify complex data + AI challenges and support end-to-end transformations, delivering future-ready solutions fast.