malwareDetector 0.1.13

Malware detector specification for NTUST isLab

malwareDetector

• Source code: https://github.com/louiskyee/malwareDetector.git
• Wiki: https://github.com/louiskyee/malwareDetector/wiki
• PyPI: https://pypi.org/project/malwareDetector/

Description

This is a malware detector specification for NTUST isLab. The malwareDetector is a base class designed for malicious software detection. It enables straightforward utilization of Python's inheritance feature. By inheriting from malwareDetector and implementing the required functions, you can achieve your specific goals. Additionally, it offers convenient configuration management. For more detailed instructions, please refer to the GitHub Wiki.

Requirements

Tool	Version	Source
Python	>= 3.10	https://www.python.org/downloads

Installation

Use the package manager pip to install malwareDetector.

• Example: pip install malwareDetector

Usage

Import

• Import class detector from malwareDetector.detector

  from malwareDetector.detector import detector
  

Example:

import numpy as np
from typing import Any
from malwareDetector.detector import detector

class subDetector(detector):
    def __init__(self, config_path=None) -> None:
        super().__init__(config_path)

    def extractFeature(self) -> Any:
        return 'This is the implementation of the extractFeature function from the derived class.'

    def vectorize(self) -> np.array:
        return 'This is the implementation of the vectorize function from the derived class.'

    def model(self, training: bool = True) -> Any:
        return 'This is the implementation of the model function from the derived class.'

    def predict(self) -> np.array:
        return 'This is the implementation of the predict function from the derived class.'

Configuration

The malwareDetector uses a configuration system that can be customized through a JSON file or command-line arguments. The default configuration file is config.json in the current directory, but you can specify a custom path when initializing the detector.

Key Configuration Classes:

• Config: Stores all external settings for the detector.
• PathConfig: Manages input and output file paths.
• FolderConfig: Handles folder configurations for data storage.
• ModelConfig: Stores model-specific parameters and hyperparameters.

For detailed information on configuration options and usage, please refer to the GitHub Wiki.