IoT spy: Security metrics for smart devices with Telegraf, InfluxDB, and Grafana
Abstract
Internet of Things (IoT) devices are ubiquitous, appearing in homes, offices, and public spaces. However, these devices often lack security features due to their fast time to market and insufficient resources for security testing. Network Automation Engineer Xenia Mountrouidou will present a set of novel security metrics based on generic IoT characteristics that relate to security features, and the architecture to collect, visualize, correlate, and alert on them with a Telegraf, InfluxDB, Grafana (TIG) stack. The goal of this architecture is to make IoT security transparent and measurable. The project, which has a testbed of home assistants, web cameras, smart lights and plugs, and phones, provides insight into how IoT devices are acting while we’re not using them.
Xenia Mountrouidou
Senior Security Researcher
Xenia Mountrouidou is a Senior Security Researcher at Cyber adAPT with versatile experience in academia and industry. She has over 10 years of research experience in network security, machine learning, and data analytics for computer networks. She enjoys writing Python scripts to automate boring things, finding interesting patterns with machine learning algorithms, and researching novel intrusion detection techniques. Her research interests revolve around network security, Internet of Things, intrusion detection, and machine learning.