Skip to main content

Universal Hyperbolic Geometry library using pure projective operations

Project description

Universal Hyperbolic Geometry (UHG) Library

A pure implementation of Universal Hyperbolic Geometry using projective operations, optimized for cybersecurity applications.

Features

Core Features

  • Pure projective geometry implementation
  • No differential geometry or manifold assumptions
  • Cross-ratio preservation throughout
  • Numerically stable operations

Advanced Features

  • UHG Metric Learning
  • Multi-head Attention Mechanism
  • Threat Correlation Engine
  • Pattern Recognition
  • Anomaly Detection

Cybersecurity Applications

  • Network Traffic Analysis
  • System Event Correlation
  • Behavioral Pattern Detection
  • Threat Intelligence Integration
  • Zero-Day Attack Detection

Installation

Basic installation:

pip install uhg

With security features:

pip install uhg[security]

With visualization tools:

pip install uhg[viz]

Quick Start

from uhg import (
    ProjectiveUHG,
    UHGMultiHeadAttention,
    ThreatCorrelation
)

# Initialize threat correlation
correlation = ThreatCorrelation(
    feature_dim=8,
    num_heads=4
)

# Create indicators
indicators = [
    ThreatIndicator(
        ThreatIndicatorType.NETWORK,
        value="suspicious_pattern",
        confidence=0.9,
        context={
            "port": 443,
            "protocol": "TCP",
            "bytes_out": 1024
        }
    ),
    ThreatIndicator(
        ThreatIndicatorType.SYSTEM,
        value="malicious_process",
        confidence=0.85,
        context={
            "pid": 1234,
            "memory_usage": 50000,
            "api_calls": 15
        }
    )
]

# Analyze relationships
groups = correlation.get_correlation_groups(indicators)
relationships = correlation.analyze_indicator_relationships(indicators)

Documentation

Full documentation is available at uhg.readthedocs.io.

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

uhg-0.2.0-py3-none-any.whl (36.7 kB view details)

Uploaded Python 3

File details

Details for the file uhg-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: uhg-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 36.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.7

File hashes

Hashes for uhg-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4c294c40459f5b97510444ad6c274fd449bc879cdc6cb6793ac30ea2e7b4f708
MD5 9a858ccd12d41582e84f5bb5ae08648b
BLAKE2b-256 98d642a65c4374b96fe5351bc21ac5f6b9e5143462c5b244e444d89f2112e94d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page