Data preparation for software vulnerability prediction: A systematic literature review
Software Vulnerability Prediction (SVP) is a data-driven technique for software quality
assurance that has recently gained considerable attention in the Software Engineering …
assurance that has recently gained considerable attention in the Software Engineering …
NLP methods in host-based intrusion detection Systems: A systematic review and future directions
Abstract Host-based Intrusion Detection System (HIDS) is an effective last line of defense for
defending against cyber security attacks after perimeter defenses (eg, Network-based …
defending against cyber security attacks after perimeter defenses (eg, Network-based …
Knowledge-driven cybersecurity intelligence: Software vulnerability coexploitation behavior discovery
Coexploitation behavior, referring to multiple software vulnerabilities being exploited jointly
by one or more exploits, brings enormous challenges to the prevention and remediation of …
by one or more exploits, brings enormous challenges to the prevention and remediation of …
Sok: Explainable machine learning for computer security applications
Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …
Deepcva: Automated commit-level vulnerability assessment with deep multi-task learning
It is increasingly suggested to identify Software Vulnerabilities (SVs) in code commits to give
early warnings about potential security risks. However, there is a lack of effort to assess …
early warnings about potential security risks. However, there is a lack of effort to assess …
Fine-grained commit-level vulnerability type prediction by CWE tree structure
Identifying security patches via code commits to allow early warnings and timely fixes for
Open Source Software (OSS) has received increasing attention. However, the existing …
Open Source Software (OSS) has received increasing attention. However, the existing …
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 Survey on Software Vulnerability Exploitability Assessment
S Elder, MR Rahman, G Fringer, K Kapoor… - ACM Computing …, 2024 - dl.acm.org
Knowing the exploitability and severity of software vulnerabilities helps practitioners
prioritize vulnerability mitigation efforts. Researchers have proposed and evaluated many …
prioritize vulnerability mitigation efforts. Researchers have proposed and evaluated many …
On the use of fine-grained vulnerable code statements for software vulnerability assessment models
Many studies have developed Machine Learning (ML) approaches to detect Software
Vulnerabilities (SVs) in functions and fine-grained code statements that cause such SVs …
Vulnerabilities (SVs) in functions and fine-grained code statements that cause such SVs …
Automatic software vulnerability assessment by extracting vulnerability elements
Software vulnerabilities take threats to software security. When faced with multiple software
vulnerabilities, the most urgent ones need to be fixed first. Therefore, it is critical to assess …
vulnerabilities, the most urgent ones need to be fixed first. Therefore, it is critical to assess …