Index of supplementary files from "Perils of Zero-Interaction Security in the Internet of Things"

Fomichev, Mikhail; Maaß, Max; Almon, Lars; Molina, Alejandro; Hollick, Matthias

doi:10.5281/zenodo.2537721

Cited by 2 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, we release the first extensible open source toolkit [9] for researching zero-interaction security, containing reference implementations of the reproduced schemes, the audio recordings of the mob/het scenario, and over 1 billion samples of labeled sensor data. We also release all data generated by our evaluation to facilitate the reproduction of our results and provide a common benchmarking baseline for future schemes.…”

Section: Discussionmentioning

confidence: 99%

“…Privacy concerns prevent us from releasing the audio data recorded in the Car and Office scenarios, but we are able to provide researchers with the audio recordings from the Mobile scenario upon request [8]. See [9] for an index of all released data and code.…”

Section: Reproducibility and Re-usabilitymentioning

confidence: 99%

“…Section 3.2). The route covers city traffic, country roads and highways between the cities of Darmstadt and Frankfurt in the state of Hesse in Germany (the actual GPS traces can be found in [9]).…”

Section: B Study Designmentioning

confidence: 99%

“…To facilitate future research, we publicly release the collected context information in an anonymized form, ground truth information, the computed context features, machine learning datasets and results for all reproduced schemes, as well as the full source code used in data collection and evaluation procedures, including metadata for reproducibility (cf. Section 3.5) [9]. We further enhance reproducibility by releasing raw audio recordings from the mobile scenario [8], making our dataset the first of its kind in the domain of ZIS.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Perils of Zero-Interaction Security in the Internet of Things

Fomichev

Maaß

Almon

et al. 2019

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

Self Cite

View full text Add to dashboard Cite

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...

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Reproducibility and Re-usabilitymentioning

confidence: 99%

Section: B Study Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Perils of Zero-Interaction Security in the Internet of Things

Fomichev

Maaß

Almon

et al. 2019

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The audio dataset [30] as well as the mobile, office, and car datasets [9] came from publicly available postings. To evaluate the audio, we created the bit stream using a commonly used algorithm [28].…”

Section: Evaluation Of Moonshinementioning

confidence: 99%

Moonshine

West

Lee

Banerjee

et al. 2021

Proceedings of the 20th International Conference on Information Processing in Sensor Networks (Co-Located With CPS-IoT Week 202

View full text Add to dashboard Cite

Context-based authentication is a method for transparently validating another device's legitimacy to join a network based on location. Devices can pair with one another by continuously harvesting environmental noise to generate a random key with no user involvement. However, there are gaps in our understanding of the theoretical limitations of environmental noise harvesting, making it difficult for researchers to build efficient algorithms for sampling environmental noise and distilling keys from that noise. This work explores the information-theoretic capacity of contextbased authentication mechanisms to generate random bit strings from environmental noise sources with known properties. Using only mild assumptions about the source process's characteristics, we demonstrate that commonly-used bit extraction algorithms extract only about 10% of the available randomness from a source noise process. We present an efficient algorithm to improve the quality of keys generated by context-based methods and evaluate it on real key extraction hardware. Moonshine is a randomness distiller which is more efficient at extracting bits from an environmental entropy source than existing methods. Our techniques nearly double the quality of keys as measured by the NIST test suite, producing keys that can be used in real-world authentication scenarios.

show abstract

Index of supplementary files from "Perils of Zero-Interaction Security in the Internet of Things"

Cited by 2 publications

References 0 publications

Perils of Zero-Interaction Security in the Internet of Things

Perils of Zero-Interaction Security in the Internet of Things

Moonshine

Contact Info

Product

Resources

About