Risk prioritization by leveraging latent vulnerability features in a contested environment

K Alperin, A Wollaber, D Ross, P Trepagnier… - Proceedings of the 12th …, 2019 - dl.acm.org
Cyber network defenders face an overwhelming volume of software vulnerabilities.
Resource limitations preclude them mitigating all but a small number of vulnerabilities on an …

Latent feature vulnerability ranking of CVSS vectors

DM Ross, AB Wollaber, PC Trepagnier - Proceedings of the Summer …, 2017 - dl.acm.org
The Common Vulnerability Scoring System (CVSS) has been widely used to provide a score
measuring the severity of software vulnerabilities. Analysts determine ordinal label …

A framework for designing vulnerability metrics

M Albanese, I Iganibo, O Adebiyi - Computers & Security, 2023 - Elsevier
Vulnerability analysis has long been used to evaluate the security posture of a system.
Different approaches, including vulnerability graphs and various vulnerability metrics, have …

Beyond heuristics: learning to classify vulnerabilities and predict exploits

M Bozorgi, LK Saul, S Savage… - Proceedings of the 16th …, 2010 - dl.acm.org
The security demands on modern system administration are enormous and getting worse.
Chief among these demands, administrators must monitor the continual ongoing disclosure …

Enhancing Vulnerability prioritization: Data-driven exploit predictions with community-driven insights

J Jacobs, S Romanosky, O Suciu… - 2023 IEEE European …, 2023 - ieeexplore.ieee.org
The number of disclosed vulnerabilities has been steadily increasing over the years. At the
same time, organizations face significant challenges patching their systems, leading to a …

Predicting cyber vulnerability exploits with machine learning

M Edkrantz, A Said - Thirteenth Scandinavian Conference on …, 2015 - ebooks.iospress.nl
For an information security manager it can be a daunting task to keep up and assess which
new cyber vulnerabilities to prioritize patching first. Every day numerous new vulnerabilities …

Detecting Complex Cyber Attacks Using Decoys with Online Reinforcement Learning

M Gutierrez - 2023 - search.proquest.com
Most vulnerabilities discovered in cybersecurity can be associated with their own singular
piece of software. I investigate complex vulnerabilities, which may require multiple software …

Toward smarter vulnerability discovery using machine learning

G Grieco, A Dinaburg - Proceedings of the 11th ACM Workshop on …, 2018 - dl.acm.org
A Cyber Reasoning System (CRS) is designed to automatically find and exploit software
vulnerabilities in complex software. To be effective, CRSs integrate multiple vulnerability …

Exploitation of vulnerabilities: a topic-based machine learning framework for explaining and predicting exploitation

K Charmanas, N Mittas, L Angelis - Information, 2023 - mdpi.com
Security vulnerabilities constitute one of the most important weaknesses of hardware and
software security that can cause severe damage to systems, applications, and users. As a …

Vulnerability prioritization: An offensive security approach

MF Bulut, A Adebayo, D Sow, S Ocepek - arXiv preprint arXiv:2206.11182, 2022 - arxiv.org
Organizations struggle to handle sheer number of vulnerabilities in their cloud
environments. The de facto methodology used for prioritizing vulnerabilities is to use …