Toward large-scale vulnerability discovery using machine learning
With sustained growth of software complexity, finding security vulnerabilities in operating
systems has become an important necessity. Nowadays, OS are shipped with thousands of …
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 …
operating secure systems. Unfortunately, only some types of vulnerabilities can be detected …
Automated software vulnerability detection with machine learning
Thousands of security vulnerabilities are discovered in production software each year, either
reported publicly to the Common Vulnerabilities and Exposures database or discovered …
reported publicly to the Common Vulnerabilities and Exposures database or discovered …
Vuldeepecker: A deep learning-based system for vulnerability detection
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 …
However, existing solutions to this problem rely on human experts to define features and …
Towards the detection of inconsistencies in public security vulnerability reports
Public vulnerability databases such as Common Vulnerabilities and Exposures (CVE) and
National Vulnerability Database (NVD) have achieved a great success in promoting …
National Vulnerability Database (NVD) have achieved a great success in promoting …
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse.
Chief among these demands, administrators must monitor the continual ongoing disclosure …
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
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 …
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
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 …
wide range of application domains. Recently, several efforts have shown success in …
Deep learning based vulnerability detection: Are we there yet?
Automated detection of software vulnerabilities is a fundamental problem in software
security. Existing program analysis techniques either suffer from high false positives or false …
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 …
hackers who discover these vulnerabilities can often exploit them for nefarious purposes …