Security Logging vs Data Volume
Effective cybersecurity depends on collecting meaningful information rather than maximizing data volume. RegulatoryTRIZ resolves this contradiction by applying risk-based logging that strengthens detection while maintaining operational efficiency.
CyberTRIZ analysis · Regulatory contradiction R072 · one of 8,235 worked contradictions published by CyberTRIZ.AI
Regulations
Business Context
Security logging is essential for detecting attacks, investigating incidents, and supporting forensic analysis. Modern organizations generate enormous volumes of logs from cloud platforms, endpoints, applications, identity services, and network devices. While extensive logging improves visibility, excessive data increases storage costs, analysis complexity, and operational overhead.
Conflict
Collecting more logs improves visibility but increases operational complexity. Limiting log collection improves efficiency but may reduce incident detection capability.
Regulatory Obligations
Log security-relevant events
Protect log integrity
Monitor critical systems
Retain logs appropriately
Review logging effectiveness
Risks
High storage costs
Inefficient investigations
Missing audit evidence
Weak incident detection
Recommended Controls
Implement risk-based logging focused on critical assets and security events. Use automated correlation, filtering, and retention policies to reduce unnecessary data while preserving evidence required for investigations.
Evidence
Logging Policy
Log Retention Schedule
SIEM Reports
Monitoring Records
Audit Questions
Are critical events logged?
Is log integrity protected?
Are logging policies reviewed regularly?
Suggested Kpis
Percentage of critical systems sending logs
Mean Time to Detect (MTTD)
Number of log-related audit findings