Results 11 to 20 of about 2,945,640 (398)
DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection [PDF]
International Symposium on Recent Advances in Intrusion Detection, 2023 We propose and release a new vulnerable source code dataset. We curate the dataset by crawling security issue websites, extracting vulnerability-fixing commits and source codes from the corresponding projects.
Yizheng Chen +4 more
semanticscholar +1 more source
Age, Culture, Humanities: An Interdisciplinary Journal, 2022 ---
Julia Henderson, Kim Sawchuk
openaire +3 more sources
Data Quality for Software Vulnerability Datasets [PDF]
International Conference on Software Engineering, 2023 The use of learning-based techniques to achieve automated software vulnerability detection has been of longstanding interest within the software security domain.
Roland Croft +2 more
semanticscholar +1 more source
Climate Change 2022 – Impacts, Adaptation and Vulnerability
, 2023 The Working Group II contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) provides a comprehensive assessment of the scientific literature relevant to climate change impacts, adaptation and vulnerability ...
Dr. Kirstin K. Holsman
semanticscholar +1 more source
Concentration of dissolved heavy metal around the Rupat waters industrial activity, Malacca Strait [PDF]
E3S Web of Conferences, 2022 The Rupat Strait is a water area located between Rupat Island and Dumai City. This area is growing rapidly which is characterized by increasing coastal residential areas, commercial centers, industries, ports and also increasing marine transportation ...
Ondara Koko +3 more
doaj +1 more source
Vulnerability detection with fine-grained interpretations [PDF]
ESEC/SIGSOFT FSE, 2021 Despite the successes of machine learning (ML) and deep learning (DL)-based vulnerability detectors (VD), they are limited to providing only the decision on whether a given code is vulnerable or not, without details on what part of the code is relevant ...
Yi Li, Shaohua Wang, T. Nguyen
semanticscholar +1 more source
Deep Learning Based Vulnerability Detection: Are We There Yet? [PDF]
IEEE Transactions on Software Engineering, 2020 Automated detection of software vulnerabilities is a fundamental problem in software security. Existing program analysis techniques either suffer from high false positives or false negatives.
Saikat Chakraborty +3 more
semanticscholar +1 more source
LineVD: Statement-level Vulnerability Detection using Graph Neural Networks [PDF]
IEEE Working Conference on Mining Software Repositories, 2022 Current machine-learning based software vulnerability detection methods are primarily conducted at the function-level. However, a key limitation of these methods is that they do not indicate the specific lines of code contributing to vulnerabilities ...
David Hin +3 more
semanticscholar +1 more source
LineVul: A Transformer-based Line-Level Vulnerability Prediction
IEEE Working Conference on Mining Software Repositories, 2022 Software vulnerabilities are prevalent in software systems, causing a variety of problems including deadlock, information loss, or system failures. Thus, early predictions of software vulnerabilities are critically important in safety-critical software ...
Michael Fu, C. Tantithamthavorn
semanticscholar +1 more source
Scientific Reports, 2022 Previous work has found that later life urban–rural differences in cognitive health can be largely explained by indicators of cognitive reserve such as education or occupation.
Dan Orsholits +11 more
doaj +1 more source