A survey on data-driven software vulnerability assessment and prioritization

THM Le, H Chen, MA Babar - ACM Computing Surveys, 2022 - dl.acm.org
Software Vulnerabilities (SVs) are increasing in complexity and scale, posing great security
risks to many software systems. Given the limited resources in practice, SV assessment and …

CySecBERT: A Domain-Adapted Language Model for the Cybersecurity Domain

M Bayer, P Kuehn, R Shanehsaz… - ACM Transactions on …, 2024 - dl.acm.org
The field of cysec is evolving fast. Security professionals are in need of intelligence on past,
current and—ideally—upcoming threats, because attacks are becoming more advanced and …

Common vulnerability scoring system prediction based on open source intelligence information sources

P Kühn, DN Relke, C Reuter - Computers & Security, 2023 - Elsevier
The number of newly published vulnerabilities is constantly increasing. Until now, the
information available when a new vulnerability is published is manually assessed by experts …

A compact vulnerability knowledge graph for risk assessment

J Yin, W Hong, H Wang, J Cao, Y Miao… - ACM Transactions on …, 2024 - dl.acm.org
Software vulnerabilities, also known as flaws, bugs or weaknesses, are common in modern
information systems, putting critical data of organizations and individuals at cyber risk. Due …

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 …

Expected exploitability: Predicting the development of functional vulnerability exploits

O Suciu, C Nelson, Z Lyu, T Bao… - 31st USENIX Security …, 2022 - usenix.org
Assessing the exploitability of software vulnerabilities at the time of disclosure is difficult and
error-prone, as features extracted via technical analysis by existing metrics are poor …

The diffusion of malicious content on Twitter and its impact on security

Y Roumani - Information & Management, 2024 - Elsevier
While Twitter remains one of the most popular social media networks within the information
security community, threat actors continue to abuse the platform to create, share, and spread …

A survey on automated software vulnerability detection using machine learning and deep learning

NS Harzevili, AB Belle, J Wang, S Wang, Z Ming… - arxiv preprint arxiv …, 2023 - arxiv.org
Software vulnerability detection is critical in software security because it identifies potential
bugs in software systems, enabling immediate remediation and mitigation measures to be …

Vision: Identifying affected library versions for open source software vulnerabilities

S Wu, R Wang, K Huang, Y Cao, W Song… - Proceedings of the 39th …, 2024 - dl.acm.org
Vulnerability reports play a crucial role in mitigating open-source software risks. Typically,
the vulnerability report contains affected versions of a software. However, despite the …

Fall of Giants: How popular text-based MLaaS fall against a simple evasion attack

L Pajola, M Conti - … IEEE European Symposium on Security and …, 2021 - ieeexplore.ieee.org
The increased demand for machine learning applications made companies offer Machine-
Learning-as-a-Service (MLaaS). In MLaaS (a market estimated 8000M USD by 2025), users …