Software vulnerability analysis and discovery using machine-learning and data-mining techniques: A survey

SM Ghaffarian, HR Shahriari - ACM computing surveys (CSUR), 2017 - dl.acm.org
Software security vulnerabilities are one of the critical issues in the realm of computer
security. Due to their potential high severity impacts, many different approaches have been …

The rise of software vulnerability: Taxonomy of software vulnerabilities detection and machine learning approaches

H Hanif, MHNM Nasir, MF Ab Razak, A Firdaus… - Journal of Network and …, 2021 - Elsevier
The detection of software vulnerability requires critical attention during the development
phase to make it secure and less vulnerable. Vulnerable software always invites hackers to …

Ai-based mobile edge computing for iot: Applications, challenges, and future scope

A Singh, SC Satapathy, A Roy, A Gutub - Arabian Journal for Science and …, 2022 - Springer
New technology is needed to meet the latency and bandwidth issues present in cloud
computing architecture specially to support the currency of 5G networks. Accordingly, mobile …

VUDENC: vulnerability detection with deep learning on a natural codebase for Python

L Wartschinski, Y Noller, T Vogel, T Kehrer… - Information and …, 2022 - Elsevier
Context: Identifying potential vulnerable code is important to improve the security of our
software systems. However, the manual detection of software vulnerabilities requires expert …

Automated identification of security issues from commit messages and bug reports

Y Zhou, A Sharma - Proceedings of the 2017 11th joint meeting on …, 2017 - dl.acm.org
The number of vulnerabilities in open source libraries is increasing rapidly. However, the
majority of them do not go through public disclosure. These unidentified vulnerabilities put …

Predicting vulnerable components: Software metrics vs text mining

J Walden, J Stuckman… - 2014 IEEE 25th …, 2014 - ieeexplore.ieee.org
Building secure software is difficult, time-consuming, and expensive. Prediction models that
identify vulnerability prone software components can be used to focus security efforts, thus …

Static analysis of information systems for IoT cyber security: a survey of machine learning approaches

I Kotenko, K Izrailov, M Buinevich - Sensors, 2022 - mdpi.com
Ensuring security for modern IoT systems requires the use of complex methods to analyze
their software. One of the most in-demand methods that has repeatedly been proven to be …

Turk-life in India

N Gupta, D Martin, BV Hanrahan, J O'Neill - Proceedings of the 2014 …, 2014 - dl.acm.org
Previous studies on Amazon Mechanical Turk (AMT), the most well-known marketplace for
microtasks, show that the largest population of workers on AMT is US based, while the …

Detecting and removing web application vulnerabilities with static analysis and data mining

I Medeiros, N Neves, M Correia - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
Although a large research effort on web application security has been going on for more
than a decade, the security of web applications continues to be a challenging problem. An …

The secret life of software vulnerabilities: A large-scale empirical study

E Iannone, R Guadagni, F Ferrucci… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Software vulnerabilities are weaknesses in source code that can be potentially exploited to
cause loss or harm. While researchers have been devising a number of methods to deal …