An Advanced Quantum-Entropy Based Ransomware Detection Mechanism
Eric Mazunin, Ronald Bishop, Elizabeth Jeanne Carter, Lawrence Knight · 2024
The evolving sophistication of encryption-based cyber threats has necessitated the development of more advanced and adaptive detection mechanisms capable of responding to increasingly covert ransomware attacks. The proposed Quantum-Entropy Dynamic Detection (QEDD) system introduces an unprecedented method for ransomware identification through quantum-entropy analysis, setting a new standard in detection sensitivity and accuracy. Unlike traditional signature-based or behavioral detection techniques, which are often limited by their reliance on predefined patterns, QEDD leverages the principles of quantum mechanics to examine entropy variations in real time, enabling the identification of novel ransomware patterns that might otherwise evade conventional methods. Through rigorous testing across diverse ransomware families, QEDD demonstrated remarkable precision, achieving high detection accuracy and minimizing false positives, even when distinguishing between malicious and benign encrypted or compressed files. The system’s adaptable architecture and rapid processing capabilities position it as a practical solution for real-time ransomware detection, enhancing cybersecurity resilience against the dynamic nature of ransomware threats. This research establishes a foundation for integrating quantum-entropy methodologies into broader cybersecurity strategies, marking a significant step forward in the evolution of threat detection technologies.