The logs you store to detect breaches cost a fortune. They're also exactly what attackers want.
RNDA encodes network traffic and behavioral data at ingest and discards the raw stream. Lower storage costs. No raw data to exfiltrate.
Request a Cybersecurity POC →The Problem
Security systems store the very data attackers want — network traffic, authentication logs, behavioral patterns. The logs created to detect breaches become the target of breaches. Raw data retention is the attack surface.
How RNDA Solves It
Behavioral similarity without behavioral data
Encode network traffic and log events to signatures on ingest. Discard raw data immediately. Detect anomalies by querying signatures against known threat patterns.
Zero raw data breach surface
When no raw logs exist, exfiltrated data has no value. Attackers who compromise the signature store get 256-byte vectors, not network traffic or credentials.
Pattern matching at scale
Query the full threat history for similar behavioral patterns in milliseconds. No decompression of raw logs required.
How RNDA Applies
Storage Elimination
Network flow logs, packet captures, and SIEM event streams compressed 169x — making multi-year log retention economically viable. A 1,000 TB enterprise SOC reduces its storage bill from $276K/year to ~$1,600/year, enabling indefinite retention of full threat history.
Privacy Protection
Compressed network metadata and endpoint behavioral data is encoded such that raw IP addresses, payloads, and identity details cannot be reconstructed. Attackers who compromise the signature store get 256-byte vectors — not network traffic, credentials, or user behavior.
Compliance Management
PCI-DSS, SOC 2, and HIPAA log retention mandates are fulfilled at a fraction of current cost, with compressed archives that pass audit queries. Regulatory requirements no longer compete with budget constraints — 7-year retention becomes as affordable as 90 days.
Intelligent Retrieval
Threat hunting across years of compressed network logs via semantic similarity search — finding lateral movement patterns and IOC matches without decompressing raw data. Proven on real PCAP captures across HTTP, HTTPS, DNS, and SSH traffic. Discrimination gap 1.04.
Collaborative Intelligence
Compressed threat intelligence and network telemetry shared across ISAC members or MSSPs without exposing raw traffic or network topology. Cross-institutional pattern matching — the signature is the evidence, not the underlying packets.
Storage Impact
Industry stat: DE-CIX internet exchanges recorded 186.9 TB of data flowing per minute globally in 2024; a large enterprise SOC ingests and retains 500–5,000 TB/year of network logs (Intelligent CIO)
1,000 TB × 20% × $276/TB ÷ 169x compression (enterprise SOC)
1,000 TB enterprise SOC saves ~$274K/year — 169x compression on real PCAP network traffic captures
Proof of Concept Results
Real data. Measured numbers. No synthetic results.
Source: Real sensor and industrial time series data
What Becomes Possible
"An endpoint generates unusual network traffic. The traffic pattern is encoded in real time and discarded. The signature is queried against 10,000+ historical threat signatures to identify similarity to known attack patterns."
Ready to see it on your data?
Every number on this page came from a real POC. Yours will be built the same way — against your actual data type, measured compression, real query latency.
Request a Cybersecurity POC →