Toward large-scale vulnerability discovery using machine learning

G Grieco, GL Grinblat, L Uzal, S Rawat, J Feist… - Proceedings of the sixth …, 2016 - dl.acm.org
With sustained growth of software complexity, finding security vulnerabilities in operating
systems has become an important necessity. Nowadays, OS are shipped with thousands of …

[PDF][PDF] Vulnerability extrapolation: Assisted discovery of vulnerabilities using machine learning

F Yamaguchi, K Rieck - 5th USENIX workshop on offensive …, 2011 - usenix.org
Rigorous identification of vulnerabilities in program code is a key to implementing and
operating secure systems. Unfortunately, only some types of vulnerabilities can be detected …

Automated software vulnerability detection with machine learning

JA Harer, LY Kim, RL Russell, O Ozdemir… - arXiv preprint arXiv …, 2018 - arxiv.org
Thousands of security vulnerabilities are discovered in production software each year, either
reported publicly to the Common Vulnerabilities and Exposures database or discovered …

Vuldeepecker: A deep learning-based system for vulnerability detection

Z Li, D Zou, S Xu, X Ou, H Jin, S Wang, Z Deng… - arXiv preprint arXiv …, 2018 - arxiv.org
The automatic detection of software vulnerabilities is an important research problem.
However, existing solutions to this problem rely on human experts to define features and …

Towards the detection of inconsistencies in public security vulnerability reports

Y Dong, W Guo, Y Chen, X Xing, Y Zhang… - 28th USENIX security …, 2019 - usenix.org
Public vulnerability databases such as Common Vulnerabilities and Exposures (CVE) and
National Vulnerability Database (NVD) have achieved a great success in promoting …

Beyond heuristics: learning to classify vulnerabilities and predict exploits

M Bozorgi, LK Saul, S Savage… - Proceedings of the 16th …, 2010 - dl.acm.org
The security demands on modern system administration are enormous and getting worse.
Chief among these demands, administrators must monitor the continual ongoing disclosure …

" You've got your nice list of bugs, now what?" vulnerability discovery and management processes in the wild

N Alomar, P Wijesekera, E Qiu, S Egelman - Sixteenth Symposium on …, 2020 - usenix.org
Organizational security teams have begun to specialize, and as a result, the existence of
red, blue, and purple teams have been used as signals for an organization's security …

How about bug-triggering paths?-understanding and characterizing learning-based vulnerability detectors

X Cheng, X Nie, N Li, H Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Machine learning and its promising branch deep learning have proven to be effective in a
wide range of application domains. Recently, several efforts have shown success in …

Deep learning based vulnerability detection: Are we there yet?

S Chakraborty, R Krishna, Y Ding… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Automated detection of software vulnerabilities is a fundamental problem in software
security. Existing program analysis techniques either suffer from high false positives or false …

Machine learning methods for software vulnerability detection

B Chernis, R Verma - Proceedings of the fourth ACM international …, 2018 - dl.acm.org
Software vulnerabilities are a primary concern in the IT security industry, as malicious
hackers who discover these vulnerabilities can often exploit them for nefarious purposes …