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TIPS: Threat Actor Informed Prioritization of Applications using SecEncoder

Authors :
Bulut, Muhammed Fatih
Tamersoy, Acar
Ahmad, Naveed
Liu, Yingqi
Greenwald, Lloyd
Publication Year :
2024

Abstract

This paper introduces TIPS: Threat Actor Informed Prioritization using SecEncoder, a specialized language model for security. TIPS combines the strengths of both encoder and decoder language models to detect and prioritize compromised applications. By integrating threat actor intelligence, TIPS enhances the accuracy and relevance of its detections. Extensive experiments with a real-world benchmark dataset of applications demonstrate TIPS's high efficacy, achieving an F-1 score of 0.90 in identifying malicious applications. Additionally, in real-world scenarios, TIPS significantly reduces the backlog of investigations for security analysts by 87%, thereby streamlining the threat response process and improving overall security posture.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2411.07519
Document Type :
Working Paper