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Found 7 papers, 4 papers with code
SECURE: Benchmarking Generative Large Language Models for Cybersecurity Advisory
Large Language Models (LLMs) have demonstrated potential in cybersecurity applications but have also caused lower confidence due to problems like hallucinations and a lack of truthfulness.
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis
However, we observe that both model predictions and feature attributions for input samples are sensitive to noise.
Looking Beyond IoCs: Automatically Extracting Attack Patterns from External CTI
The framework characterizes attack patterns by capturing the phases of an attack in Android and enterprise networks and systematically maps them to the MITRE ATT\&CK pattern framework.
SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and Usability
Interpretability, trustworthiness, and usability are key considerations in high-stake security applications, especially when utilizing deep learning models.
CyNER: A Python Library for Cybersecurity Named Entity Recognition
Open Cyber threat intelligence (OpenCTI) information is available in an unstructured format from heterogeneous sources on the Internet.
Adversarial Patterns: Building Robust Android Malware Classifiers
These approaches have resulted in a multitude of attack and defense techniques and the emergence of a field known as `adversarial machine learning.'
Multi-Label Classification of Thoracic Diseases using Dense Convolutional Network on Chest Radiographs
Traditional methods of identifying pathologies in X-ray images rely heavily on skilled human interpretation and are often time-consuming.
