Skip to main content

Universal Hyperbolic Geometry Library

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 Distribution

uhg-0.3.2.tar.gz (165.9 kB view details)

Uploaded Source

Built Distribution

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

uhg-0.3.2-py3-none-any.whl (60.3 kB view details)

Uploaded Python 3

File details

Details for the file uhg-0.3.2.tar.gz.

File metadata

  • Download URL: uhg-0.3.2.tar.gz
  • Upload date:
  • Size: 165.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.7

File hashes

Hashes for uhg-0.3.2.tar.gz
Algorithm Hash digest
SHA256 4d6ddaa4794135f98f1659d93eb0ff51ff5fa4e2651fecf559e1bceaa0871ea3
MD5 241075f250829f10e258204699df0221
BLAKE2b-256 09d9bea3eb37f5922d524ecd8f3fd8db704d833c1d742d41990de69aae386dcd

See more details on using hashes here.

File details

Details for the file uhg-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: uhg-0.3.2-py3-none-any.whl
  • Upload date:
  • Size: 60.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.12.7

File hashes

Hashes for uhg-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 4ce67a52e8e5b5244820e55e953aec9ded38288f493334a9684e07ac99f2baa0
MD5 2b8012e67135d5575ad5ef085455187f
BLAKE2b-256 3634235d27143503a4140d61d4acc40029e9be906ff4162ec361bd47fd0d9c3f

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