From One Attack Domain to Another: Contrastive Transfer Learning with Siamese Networks for APT Detection

Advanced Persistent Threats APT pose a major cybersecurity challenge due to their stealth, persistence, and adaptability. Traditional machine learning detectors struggle with class imbalance, high dimensional features, and scarce real world traces. They often lack transferability-performing well ...

VOLTRON: Detecting Unknown Malware Using Graph-Based Zero-Shot Learning

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 to detect these threats, their reliance on large labeled datasets limits their effectiveness against emerging,...

Manipulating Weights in Face-Recognition AI Systems

Interesting research: "Facial Misrecognition Systems: Simple Weight Manipulations Force DNNs to Err Only on Specific Persons": Abstract: In this paper we describe how to plant novel types of backdoors in any facial recognition model based on the popular architecture of deep Siamese neural network...