Identifying the family of a newly observed malware sample is a core task in threat intelligence, yet conventional classifiers must be retrained whenever a new family appears. This chapter develops an image-based metric learning approach that instead learns to extract discriminative neural fingerprints--fixed-length emb...
Manasa Deshagouni, Sayma Akther, Martin Jurecek et al.· 0 citations
In this work, we propose a system to recognize human activities using the accelerometer and gyroscope of a smartphone, which has the potential to be used as a tool to monitor health conditions in real time. We use the UCI HAR dataset to assess the performance of different classifiers, such as Decision Tree, Naive Bayes...
Nathan H Choi, Lawrence Cuenco, Anas Durrani et al.· International Conference on...· 0 citations
Wearable sensor-based alcohol detection requires methods that are aligned with the available label structure, sensing modality, and temporal scale. This paper presents a comparative study across two alcohol sensing settings. The first setting uses the Bar Crawl dataset, where smartphone accelerometer data must be inter...