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Found 7 papers, 1 papers with code
Automated CVE Analysis for Threat Prioritization and Impact Prediction
Unfortunately, this manual analysis presents a major bottleneck in the vulnerability analysis process, leading to slowdowns in proactive cybersecurity efforts and the potential for inaccuracies due to human errors.
CVE-driven Attack Technique Prediction with Semantic Information Extraction and a Domain-specific Language Model
This automated correlation facilitates the creation of labeled data, essential for categorizing novel threat actions into threat functionality classes and TTPs.
SecureBERT: A Domain-Specific Language Model for Cybersecurity
Natural Language Processing (NLP) has recently gained wide attention in cybersecurity, particularly in Cyber Threat Intelligence (CTI) and cyber automation.
ThreatZoom: CVE2CWE using Hierarchical Neural Network
The Common Vulnerabilities and Exposures (CVE) represent standard means for sharing publicly known information security vulnerabilities.
Active Defense Against Social Engineering: The Case for Human Language Technology
We describe a system that supports natural language processing (NLP) components for active defenses against social engineering attacks.
The Panacea Threat Intelligence and Active Defense Platform
We describe Panacea, a system that supports natural language processing (NLP) components for active defenses against social engineering attacks.
Host-based anomaly detection using Eigentraces feature extraction and one-class classification on system call trace data
This paper proposes a methodology for host-based anomaly detection using a semi-supervised algorithm namely one-class classifier combined with a PCA-based feature extraction technique called Eigentraces on system call trace data.
