A lightweight double-stage scheme to identify malicious DNS over HTTPS traffic using a hybrid learning approach
The Domain Name System (DNS) protocol essentially translates domain names to IP
addresses, enabling browsers to load and utilize Internet resources. Despite its major role …
addresses, enabling browsers to load and utilize Internet resources. Despite its major role …
Effective one-class classifier model for memory dump malware detection
M Al-Qudah, Z Ashi, M Alnabhan… - Journal of Sensor and …, 2023 - mdpi.com
Malware complexity is rapidly increasing, causing catastrophic impacts on computer
systems. Memory dump malware is gaining increased attention due to its ability to expose …
systems. Memory dump malware is gaining increased attention due to its ability to expose …
Explainable ensemble learning based detection of evasive malicious pdf documents
PDF has become a major attack vector for delivering malware and compromising systems
and networks, due to its popularity and widespread usage across platforms. PDF provides a …
and networks, due to its popularity and widespread usage across platforms. PDF provides a …
[HTML][HTML] A study of the relationship of malware detection mechanisms using Artificial Intelligence
J Song, S Choi, J Kim, K Park, C Park, J Kim, I Kim - ICT Express, 2024 - Elsevier
Implementation of malware detection using Artificial Intelligence (AI) has emerged as a
significant research theme to combat evolving various types of malwares. Researchers …
significant research theme to combat evolving various types of malwares. Researchers …
Explainable AI model for PDFMal detection based on gradient boosting model
Portable document formats (PDFs) are widely used for document exchange due to their
widespread usage and versatility. However, PDFs are highly vulnerable to malware attacks …
widespread usage and versatility. However, PDFs are highly vulnerable to malware attacks …
Securing IoT devices running PureOS from ransomware attacks: leveraging hybrid machine learning techniques
Internet-enabled (IoT) devices are typically small, low-powered devices used for sensing
and computing that enable remote monitoring and control of various environments through …
and computing that enable remote monitoring and control of various environments through …
Malicious pdf detection based on machine learning with enhanced feature set
PDF is one of the most popular document file formats due to its flexibility, platform
independence and ability to embed different types of content. Over the years, PDF has …
independence and ability to embed different types of content. Over the years, PDF has …
Field-Scale Winter Wheat Growth Prediction Applying Machine Learning Methods with Unmanned Aerial Vehicle Imagery and Soil Properties
Monitoring crop growth conditions during the growing season provides information on
available soil nutrients and crop health status, which are important for agricultural …
available soil nutrients and crop health status, which are important for agricultural …
Spyware Identification for Android Systems Using Fine Trees
Android operating system (OS) has been recently featured as the most commonly used and
ingratiated OS for smartphone ecosystems. This is due to its high interoperability as an open …
ingratiated OS for smartphone ecosystems. This is due to its high interoperability as an open …
A Novel Feature Encoding Scheme for Machine Learning Based Malware Detection Systems.
Malware detection is an ever-evolving area given that the strides in the detection capabilities
being matched by radical attempts to bypass the detection. As the sophistication of malware …
being matched by radical attempts to bypass the detection. As the sophistication of malware …