Certis: Cloud Asset Management & Threat Evaluation Using Behavioral Fingerprinting at Application Layer  

作　　者：Kumardwij Bhatnagar Vijay K. Madisetti Kumardwij Bhatnagar;Vijay K. Madisetti(School of Cybersecurity & Privacy, Georgia Institute of Technology, Atlanta, GA, USA)

机构地区：[1]School of Cybersecurity & Privacy, Georgia Institute of Technology, Atlanta, GA, USA

出　　处：《Journal of Software Engineering and Applications》2024年第6期474-486,共13页软件工程与应用（英文）

摘　　要：This paper introduces Certis, a powerful framework that addresses the challenges of cloud asset tracking, management, and threat detection in modern cybersecurity landscapes. It enhances asset identification and anomaly detection through SSL certificate parsing, cloud service provider integration, and advanced fingerprinting techniques like JARM at the application layer. Current work will focus on cross-layer malicious behavior identification to further enhance its capabilities, including minimizing false positives through AI-based learning techniques. Certis promises to offer a powerful solution for organizations seeking proactive cybersecurity defenses in the face of evolving threats.This paper introduces Certis, a powerful framework that addresses the challenges of cloud asset tracking, management, and threat detection in modern cybersecurity landscapes. It enhances asset identification and anomaly detection through SSL certificate parsing, cloud service provider integration, and advanced fingerprinting techniques like JARM at the application layer. Current work will focus on cross-layer malicious behavior identification to further enhance its capabilities, including minimizing false positives through AI-based learning techniques. Certis promises to offer a powerful solution for organizations seeking proactive cybersecurity defenses in the face of evolving threats.

关 键 词：Certis SSL Certificate Parsing JARM Fingerprinting Anomaly Detection Proactive Defense 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]