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Entropy and the Second Law of Thermodynamics01:20

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Comparison of Entropy Calculation Methods for Ransomware Encrypted File Identification.

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This study evaluates 53 entropy calculation methods to detect crypto-ransomware. It identifies superior entropy techniques for distinguishing encrypted files from normal data, improving ransomware detection accuracy.

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Data Analysis

Background:

  • Crypto-ransomware attacks system availability by encrypting data.
  • Current detection methods often use file entropy but lack justification for technique selection.
  • Shannon entropy is commonly used but may not be optimal for identifying encrypted files.

Purpose of the Study:

  • To compare the accuracy of various entropy calculation methods for detecting crypto-ransomware encrypted files.
  • To identify the most effective entropy techniques for differentiating encrypted data from other file types.
  • To investigate the potential of hybrid approaches for enhanced detection accuracy.

Main Methods:

  • Evaluated 53 distinct tests in two phases: candidate identification and thorough evaluation.
  • Utilized the NapierOne dataset with thousands of file types and crypto-ransomware examples.
  • Tested 11 candidate entropy techniques on over 270,000 files, performing nearly three million calculations.

Main Results:

  • Identified significant differences in the accuracy of various entropy methods for differentiating encrypted files.
  • Determined the overall accuracy of each test in identifying crypto-ransomware encrypted files.
  • Investigated the effectiveness of combining multiple tests in a hybrid approach.

Conclusions:

  • Certain entropy calculation methods are more effective than others for detecting crypto-ransomware.
  • The choice of entropy calculation technique significantly impacts the accuracy of encrypted file identification.
  • Hybrid approaches may offer improved accuracy in ransomware detection.