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Area of Science:

  • Computer Science
  • Cybersecurity
  • Software Engineering

Background:

  • Inconsistent software development standards often introduce vulnerabilities impacting cryptographic integrity.
  • Flawed encryption processes and missing cryptographic mechanisms weaken overall application security.

Purpose of the Study:

  • To introduce a robust method for detecting vulnerabilities in cryptographic applications.
  • To enhance the security and resilience of software through improved vulnerability detection.

Main Methods:

  • Utilizing dynamic and static analysis techniques.
  • Developing a layered and modular model to map cryptographic function call flows.
  • Employing a cryptographic function dominance tree for systematic analysis.

Main Results:

  • The proposed method accurately identifies and localizes potential security issues.
  • Experimental findings show enhanced accuracy and comprehensiveness in vulnerability detection.
  • The approach improves the security and resilience of cryptographic implementations.

Conclusions:

  • The integrated dynamic and static analysis method effectively detects cryptographic vulnerabilities.
  • The cryptographic function dominance tree approach systematically minimizes integrity breaches.
  • This strategy significantly strengthens the security posture of software applications.