Source: Help Net Security
Author: Help Net Security
URL: https://www.helpnetsecurity.com/2025/03/25/security-data-hygiene/
# ONE SENTENCE SUMMARY:
Modern security teams must clean, enrich, and prioritize security data to improve detection, reduce costs, and enhance efficiency.
# MAIN POINTS:
1. Security operations suffer from bloated, noisy data that hinders detection and response effectiveness.
2. Indiscriminate data hoarding inflates costs and overwhelms analysts with irrelevant telemetry.
3. Manual rule tuning is outdated; AI and automation should drive dynamic, adaptive data processing.
4. SIEM storage costs can be reduced using tiered storage, deduplication, and preprocessing strategies.
5. Prioritizing high-fidelity data over sheer volume leads to better detection and operational efficiency.
6. Contextual enrichment using ontologies and threat models accelerates investigation and decision-making.
7. Alerts must be explainable and tied to broader narratives for meaningful, actionable insights.
8. Modern security telemetry pipelines streamline ingestion, enrichment, and routing before hitting analytics tools.
9. Schema-on-read and SOCless models enable flexible, scalable security data analysis without monolithic SIEMs.
10. Effective data hygiene ensures SOC teams focus on real threats, reducing burnout and improving outcomes.
# TAKEAWAYS:
1. Shift from collecting all data to curating and enriching only what matters for security value.
2. Embrace automation and AI to replace brittle, manually tuned detection rules.
3. Use cost-effective storage and preprocessing to manage log volume without sacrificing insight.
4. Leverage context and explainability to turn raw alerts into meaningful threat narratives.
5. Invest in purpose-built security data engineering tools for streamlined, scalable operations.