3 papers
cs.CR2025
VOLTRON: Detecting Unknown Malware Using Graph-Based Zero-Shot Learning
M. Tahir Akdeniz, Zeynep YeÅilkaya, Ä°. Enes Köse +2
The persistent threat of Android malware presents a serious challenge to the security of millions of users globally. While many machine learning-based methods have been developed t…
cs.CR2025
A Comprehensive Analysis of Adversarial Attacks against Spam Filters
Esra HotoÄlu, Sevil Sen, Burcu Can
Deep learning has revolutionized email filtering, which is critical to protect users from cyber threats such as spam, malware, and phishing. However, the increasing sophistication…
cs.CR2025
Explainable Android Malware Detection and Malicious Code Localization Using Graph Attention
Merve Cigdem Ipek, Sevil Sen
With the escalating threat of malware, particularly on mobile devices, the demand for effective analysis methods has never been higher. While existing security solutions, including…