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Found 4 papers, 2 papers with code
Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection
Quantum machine learning (QML) is an emerging field of research that leverages quantum computing to improve the classical machine learning approach to solve complex real world problems.
Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning Algorithms
Our goal is to distinguish the performance between QNN and NN and to conduct the experiment, we develop two different models for QNN and NN by utilizing Pennylane for quantum and TensorFlow and Keras for traditional respectively.
Malware Detection and Prevention using Artificial Intelligence Techniques
The comprehension of this synthesis shall help researchers for further research on malware detection and prevention using AI.
Security Smells in Infrastructure as Code Scripts
We observe agreement for 130 of the responded 187 bug reports, which suggests the relevance of security smells for IaC scripts amongst practitioners.
Cryptography and Security Software Engineering
