Abstract Voice phishing (vishing) attacks represent a growing threat in cybersecurity, with attackers increasingly using sophisticated audio manipulation techniques to deceive victims. This paper presents a novel approach to automatically detecting voice phishing attacks using large audio models. We develop a comprehensive framework that leverages advanced audio processing techniques and machine learning to identify malicious voice communications in real-time.
Jan 1, 2026
A multi-task relation learning approach for extracting protected health information from multilingual hacker communities.
Jan 1, 2026
Pioneering research on the application of large language models for cybersecurity text analysis, threat detection, and security intelligence.
Jan 1, 2024
A computational design science approach for improving threat mitigation through cybersecurity risk management.
Jan 1, 2024
A deep transfer learning approach for creating proactive cyber threat intelligence using hacker exploit labels.
Jan 1, 2024
Developed innovative computational design science approaches for cybersecurity research, focusing on artifact design, evaluation, and validation methodologies.
Jun 1, 2023
A multi-label transformer approach for mapping exploit code to the MITRE ATT&CK framework.
Jan 1, 2023
A graph embedding approach for disrupting ransomware actors on the Bitcoin blockchain.
Jan 1, 2023
Developed a comprehensive framework for automated cyber threat intelligence using large-scale text analytics and machine learning techniques.
Jan 1, 2023