Search Results for author:
Found 2 papers, 1 papers with code
Augmenting Rule-based DNS Censorship Detection at Scale with Machine Learning
In this paper, we explore how machine learning (ML) models can (1) help streamline the detection process, (2) improve the potential of using large-scale datasets for censorship detection, and (3) discover new censorship instances and blocking signatures missed by existing heuristic methods.
GRAVITAS: Graphical Reticulated Attack Vectors for Internet-of-Things Aggregate Security
Internet-of-Things (IoT) and cyber-physical systems (CPSs) may consist of thousands of devices connected in a complex network topology.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
