  The Internet of Things is in constant growth, with millions of devices used
every day in our homes and workplaces to ease our lives. Such a strict
coexistence between humans and smart devices makes the latter digital witnesses
of our every-day lives through their sensor systems. This opens up to a new
area of digital investigation named IoT Forensics, where digital traces
produced by smart devices (network traffic, in primis) are leveraged as
evidences for forensic purposes. It is therefore important to create tools able
to capture, store and possibly analyse easily such digital traces to ease the
job of forensic investigators. This work presents one of such tools, named
Feature-Sniffer, which is thought explicitly for Wi-Fi enabled smart devices
used in Smart Building/Smart Home scenarios. Feature-Sniffer is an add-on for
OpenWrt-based access points and allows to easily perform online traffic feature
extraction, avoiding to store large PCAP files. We present Feature-Sniffer with
an accurate description of the implementation details, and we show its possible
uses with practical examples for device identification and activity
classification from encrypted traffic produced by IoT cameras. We release
Feature-Sniffer publicly for reproducible research.
