Performance Analysis of a Privacy-Preserving Frame Sniffer on a Raspberry Pi

Abstract

networks are an abundant data source that may serve different applications such as epidemic tracking and prevention, disaster response, crowdsensing, or ubiquitous urban services. Nevertheless, collecting and exploiting such data brings many privacy liabilities, considering that each transmitted frame has the MAC address (a unique device identifier) of the corresponding personal device, also considered sensitive information. Literature has shown that the MAC randomization performed by manufacturers of phones is not enough to protect devices' identification. Data obfuscation is a promising solution to avoid storing advertised identifiers of devices and prevent attackers from acquiring sensitive data. Obfuscating such identifiers while also being able to differentiate frames sent by different devices poses a significant challenge for frame capturing by low-resource IoT devices in real-time. This paper illustrates the impact of on-the-fly hashing as an obfuscating measure to protect people's privacy. Since no popular off-the-shelf sniffer (using wireshark or tcpdump) allows for on-the-fly hashing, we build upon the scapy library a custommade sniffer capable of hashing the required data needed to protect user privacy. We demonstrate the viability of this privacypreserving IoT sniffer on a Raspberry Pi platform.