CRLX: X.509 CRL Acceleration Framework

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1. Project Overview

CRLX is an open-source framework designed to accelerate X.509 Certificate Revocation List (CRL) processing. It addresses the key bottlenecks of traditional RFC 5280 CRLs:

• Computational latency: Expensive ASN.1 decoding and linear lookup.
• Security trade-offs: Bloom filter or compressed CRL methods introduce false positives.

CRLX implements a non-probabilistic, client-side optimization layer:

• ASN.1 decoding is done once upon CRL download.
• Revoked serial numbers are stored in a hash-based index (O(1) lookup).
• Works with both synthetic and real CRLs with 100% fidelity.

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2. Project Objectives

Phase	Objective	Metric
Profiling	Quantify latency in legacy CRL lookups	L_decode, L_fetch measurements
Acceleration	Achieve O(1) lookup speed	Speedup factor, storage reduction
Visualization	Validate correctness and high fidelity	Interactive dashboard with metrics

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3. Dataset

• Synthetic CRLs: Generated in Colab (3 certificates revoked)
• Real CRLs: Example CRL with 36 revoked certificates
  • Sample revoked serials:
    [343221542082308252812471151435050411029562276936, 652150439487329841487760055844176057896109436344, ...]

Note: CRLX can scale to large CRLs (thousands+ revocations) due to hash-based indexing.

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4. How to Run (Google Colab)

1. Open the notebook

2. Run all cells to:

   • Generate synthetic CRLs
   • Build CRLX index
   • Upload real CRL (optional)
   • View performance metrics in interactive dashboard

3. Optional: install dependencies locally:

pip install -r requirements.txt

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5. Implementation Steps

1. Directory setup: /crlx, /data, /Colab, /docs, /screenshots
2. Generate synthetic CRLs and store them in /data
3. Parse CRL files using crlx/crl_parser.py
4. Build accelerated index using crlx/crlx_index.py
5. Query lookup and compare with legacy linear search
6. Interactive visualization: latency, speedup, cache size, staleness

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6. Results

Metric	Synthetic CRL	Real CRL (36 revoked)
Total CRLs	3	1
Total revoked certs	3	36
Cache size (bytes)	1,301	12,450
Avg lookup speedup	11.57x	1.02x

Dashboard visualizations: Latency decomposition, gauge indicators, staleness indicator, summary table.

Screenshots / graphs can be added in /screenshots.

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7. Architecture Flow

CRL Download → ASN.1 Decode (once) → Build Hash Index → O(1) Lookup → Dashboard Metrics

• Works client-side only, requires no changes to global PKI.

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8. References / Research

• RFC 5280 – Internet X.509 PKI CRL Profile
• TinyCR: Efficient CRL lookups in constrained environments
• C2RL: Compressed CRLs using Bloom filters
• AWS CRL scaling research (latency & caching analysis)
• Micali, Hash-tree based revocation schemes

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