475 citations · 555 across the 41 of their papers we have counts for
6 papers · 2 filters
Feature Analysis of Encrypted Malicious Traffic
Anish Singh Shekhawat, Fabio Di Troia, Mark Stamp
In recent years there has been a dramatic increase in the number of malware attacks that use encrypted HTTP traffic for self-propagation or communication. Antivirus software and fi…
A Comparison of Adversarial Learning Techniques for Malware Detection
Pavla Louthánová, Matouš Kozák, Martin Jureček +1
Machine learning has proven to be a useful tool for automated malware detection, but machine learning models have also been shown to be vulnerable to adversarial attacks. This arti…
Hidden Markov Models with Random Restarts vs Boosting for Malware Detection
Aditya Raghavan, Fabio Di Troia, Mark Stamp
Effective and efficient malware detection is at the forefront of research into building secure digital systems. As with many other fields, malware detection research has seen a dra…
A Natural Language Processing Approach to Malware Classification
Ritik Mehta, Olha Jurečková, Mark Stamp
Many different machine learning and deep learning techniques have been successfully employed for malware detection and classification. Examples of popular learning techniques in th…
Steganographic Capacity of Deep Learning Models
Lei Zhang, Dong Li, Olha Jurečková +1
As machine learning and deep learning models become ubiquitous, it is inevitable that there will be attempts to exploit such models in various attack scenarios. For example, in a s…
Creating Valid Adversarial Examples of Malware
Matouš Kozák, Martin Jureček, Mark Stamp +1
Machine learning is becoming increasingly popular as a go-to approach for many tasks due to its world-class results. As a result, antivirus developers are incorporating machine lea…