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A survey on data-driven software vulnerability assessment and prioritization
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 …
risks to many software systems. Given the limited resources in practice, SV assessment and …
CySecBERT: A Domain-Adapted Language Model for the Cybersecurity Domain
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 …
current and—ideally—upcoming threats, because attacks are becoming more advanced and …
Common vulnerability scoring system prediction based on open source intelligence information sources
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 …
information available when a new vulnerability is published is manually assessed by experts …
A compact vulnerability knowledge graph for risk assessment
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 …
information systems, putting critical data of organizations and individuals at cyber risk. Due …
Enhancing vulnerability prioritization: Data-driven exploit predictions with community-driven insights
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 …
same time, organizations face significant challenges patching their systems, leading to a …
Expected exploitability: Predicting the development of functional vulnerability exploits
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 …
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 …
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
Software vulnerability detection is critical in software security because it identifies potential
bugs in software systems, enabling immediate remediation and mitigation measures to be …
bugs in software systems, enabling immediate remediation and mitigation measures to be …
Vision: Identifying affected library versions for open source software vulnerabilities
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 …
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
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 …
Learning-as-a-Service (MLaaS). In MLaaS (a market estimated 8000M USD by 2025), users …