4 papers
Adversarial Co-Evolution of Malware and Detection Models: A Bilevel Optimization Perspective
Olha JureÄková, Martin JureÄek, MatouÅ¡ Kozák +1
Machine learning-based malware detectors are increasingly vulnerable to adversarial examples. Traditional defenses, such as one-shot adversarial training, often fail against adapti…
Detecting and Explaining Malware Family Evolution Using Rule-Based Drift Analysis
Olha JureÄková, Martin JureÄek
Malware detection and classification into families are critical tasks in cybersecurity, complicated by the continual evolution of malware to evade detection. This evolution introdu…
Malware Classification using a Hybrid Hidden Markov Model-Convolutional Neural Network
Ritik Mehta, Olha Jureckova, Mark Stamp
The proliferation of malware variants poses a significant challenges to traditional malware detection approaches, such as signature-based methods, necessitating the development of…
Online Clustering of Known and Emerging Malware Families
Olha JureÄková, Martin JureÄek, Mark Stamp
Malware attacks have become significantly more frequent and sophisticated in recent years. Therefore, malware detection and classification are critical components of information se…