Perils of Zero-Interaction Security in the Internet of Things

Abstract

The Internet of Things (IoT) demands authentication systems which can provide both security and usability. Recent research utilizes the rich sensing capabilities of smart devices to build security schemes operating without human interaction, such as zero-interaction pairing (ZIP) and zero-interaction authentication (ZIA). Prior work proposed a number of ZIP and ZIA schemes and reported promising results. However, those schemes were often evaluated under conditions which do not reflect realistic IoT scenarios. In addition, drawing any comparison among the existing schemes is impossible due to the lack of a common public dataset and unavailability of scheme implementations.In this paper, we address these challenges by conducting the first large-scale comparative study of ZIP and ZIA schemes, carried out under realistic conditions. We collect and release the most comprehensive dataset in the domain to date, containing over 4250 hours of audio recordings and 1 billion sensor readings from three different scenarios, and evaluate five state-ofthe-art schemes based on these data. Our study reveals that the effectiveness of the existing proposals is highly dependent on the scenario they are used in. In particular, we show that these schemes are subject to error rates between 0.6% and 52.8%. 10:2 • M. Fomichev et al.often called context information [22]. This information is used to build context-based security schemes operating without user interaction such as zero-interaction pairing (ZIP) [20,24,39] and zero-interaction authentication (ZIA) [14,28,36]. We further refer to both as zero-interaction security (ZIS) schemes.The security of ZIS schemes is based on the assumption that context information has high entropy, changes frequently, and is unpredictable from outside the specified environment [31]. Context information, obtained from the ambient environment of an IoT device, is used to derive a shared secret key between colocated devices in ZIP or to serve as a proof of physical proximity between devices in ZIA. For example, similarity in ambient audio sensed by two colocated devices was successfully used in both ZIP [24] and ZIA [14], with the latter scheme becoming part of a commercial product [11]. Other research explored the applicability of different context information in ZIS schemes: temperature, humidity, pressure, and luminosity [20,28], magnetic fields, acceleration and rotation rates [23,26], as well as observed WiFi and Bluetooth beacons [36].ZIS schemes have three main advantages compared to traditional approaches. First, they offer high usability by minimizing user involvement in pairing and authentication procedures. Second, ZIS schemes can scale to a large number of devices, including those that do not share a common sensing modality [13]. Third, ZIS schemes can be built on top of devices' sensing capabilities, reducing modification overhead and facilitating interoperability.Despite the great potential of ZIS schemes to enable a more secure and usable IoT, prior work raised questions about their practica...

Zero-Interaction Security-Towards Sound Experimental Validation

“…In this paper, we discussed the challenges we encountered when reproducing and validating five state-of-the-art Zero-Interaction Security (ZIS) schemes on a realistic dataset [1]. They included problems in understanding and replicating the published schemes due to ambiguous descriptions and a lack of published source code and datasets, issues with the data collection and processing, and the subsequent release of the dataset.…”

“…Reproducing the work of others, collecting data and releasing it with the codebase were the main contributions of our study [1], which are often considered "not challenging" or "not novel" enough by reviewers, and hence, fall largely into the category of (almost) unpublishable results per se. In this article, we want to illustrate the difficulties we faced in our study by first describing the challenges encountered when reproducing five ZIS schemes such as the absence of the source code and documentation, ambiguities, and unspecified parameters.…”

Short-Range Audio Channels Security: Survey of Mechanisms, Applications, and Research Challenges

“…Finally, as experimentally demonstrated by the authors in [69], the effectiveness of audiobased TFA schemes is strongly dependent on the particular physical context where they are applied. For instance, considering the Sound-Proof scheme proposed in [57], the authors in [69] discovered very different values of EERs not only in different physical contexts (e.g., car, static office, and office with mobile heterogeneous devices), but also when each physical context is in a different condition. For instance, when deployed in a car, Sound-Proof achieves an equal error rate of 0.071 in a city scenario, while its performance drops down to EER values of 0.124 when the car is parked, by using the same setup of the protocol parameters.…”

“…The heterogeneity of microphones and speakers, as well as their different tolerance to the noise in different application scenarios, take part in degrading the performance of audiobased pairing schemes when moved away from a suitable application scenario. For instance, as shown by the authors in [69], the same Zero-Interaction audio-based solution report very different performance in indoor and outdoor scenarios. To overcome these limitations, researchers should design coefficient and comparison methods able to both remove inherent inaccuracies in the devices' hardware, and evaluate similarities and differences between recorded sounds in heterogeneous application domains.…”

Safer

“…While the growing number of connected devices enable powerful new use cases, they introduce vulnerabilities in networks and open them up for attacks that risk, at the very least, to jeopardize users' privacy. This is becoming a growing concern of the UbiComp community that recently investigated IoT device security schemes operating without user intervention [14]; needs in control and accountability of IoT devices in the smart home [20]; and privacy and control over intimate data recorded by connected devices [24].…”