Ransomware threat success factors, taxonomy, and countermeasures: A survey and research directions
Ransomware is a malware category that exploits security mechanisms such as cryptography
in order to hijack user files and related resources and demands money in exchange for the …
in order to hijack user files and related resources and demands money in exchange for the …
Measuring and modeling the label dynamics of online {Anti-Malware} engines
VirusTotal provides malware labels from a large set of anti-malware engines, and is heavily
used by researchers for malware annotation and system evaluation. Since different engines …
used by researchers for malware annotation and system evaluation. Since different engines …
Semantics-based online malware detection: Towards efficient real-time protection against malware
Recently, malware has increasingly become a critical threat to embedded systems, while the
conventional software solutions, such as antivirus and patches, have not been so successful …
conventional software solutions, such as antivirus and patches, have not been so successful …
Bugram: bug detection with n-gram language models
To improve software reliability, many rule-based techniques have been proposed to infer
programming rules and detect violations of these rules as bugs. These rule-based …
programming rules and detect violations of these rules as bugs. These rule-based …
xfuzz: Machine learning guided cross-contract fuzzing
Smart contract transactions are increasingly interleaved by cross-contract calls. While many
tools have been developed to identify a common set of vulnerabilities, the cross-contract …
tools have been developed to identify a common set of vulnerabilities, the cross-contract …
[HTML][HTML] A machine learning approach to detection of JavaScript-based attacks using AST features and paragraph vectors
Websites attract millions of visitors due to the convenience of services they offer, which
provide for interesting targets for cyber attackers. Most of these websites use JavaScript (JS) …
provide for interesting targets for cyber attackers. Most of these websites use JavaScript (JS) …
A systematic literature review and quality analysis of Javascript malware detection
Context: JavaScript (JS) is an often-used programming language by millions of web pages
and is also affected by thousands of malicious attacks. Objective: In this investigation, we …
and is also affected by thousands of malicious attacks. Objective: In this investigation, we …
Wobfuscator: Obfuscating javascript malware via opportunistic translation to webassembly
To protect web users from malicious JavaScript code, various malware detectors have been
proposed, which analyze and classify code as malicious or benign. State-of-the-art detectors …
proposed, which analyze and classify code as malicious or benign. State-of-the-art detectors …
An empirical study on the effects of obfuscation on static machine learning-based malicious javascript detectors
K Ren, W Qiang, Y Wu, Y Zhou, D Zou… - Proceedings of the 32nd …, 2023 - dl.acm.org
Machine learning is increasingly being applied to malicious JavaScript detection in
response to the growing number of Web attacks and the attendant costly manual …
response to the growing number of Web attacks and the attendant costly manual …
Active automata learning in practice: an annotated bibliography of the years 2011 to 2016
Active automata learning is slowly becoming a standard tool in the toolbox of the software
engineer. As systems become ever more complex and development becomes more …
engineer. As systems become ever more complex and development becomes more …