3,703 research outputs found
Accurate acoustic ranging system using android smartphones
ACCURATE ACOUSTIC RANGING SYSTEM USING ANDROID SMARTPHONES
By Mohammadbagher Fotouhi, Master of Science
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University
Virginia Commonwealth University 2017
Major Director: Dr. Ruixin Niu, Associate Professor of Department of Electrical and Computer Engineering
In this thesis, we present the design, implementation, and evaluation of an android ranging system, a high-accuracy acoustic-based ranging system which allows two android mobile phones to learn their physical distance from each other.
In this system we propose a practical solution for accurate ranging based on acoustic communication between speakers and microphones on two smartphones. Using the audible-band acoustic signal with the Wi-Fi assistance without the sound disturbance is promising for large deployment. Our method is a pure software-based solution and uses only the most basic set of commodity hardware: a speaker, a microphone, and Wi-Fi communication. So it is readily applicable to many commercial-off-the-shelf mobile devices like cell phones.
Our system is the result of several design goals, including user privacy, decentralized administration, and low cost. Rather than relying on any centralized management which tracks the user’s location to help them find their distance, our system helps devices learn their distance from each other without advertising their location information with any centralized management.
Compared to alternatives that require special-purpose hardware or pre-existence of precision location infrastructure , our system is applicable on most of off-the-shelf components so it is a commodity-based solution will obviously have wider applications and is cost effective.
Currently, two smartphones are used to estimate the distance between them through Wi-Fi and audio communications. The basic idea is estimating the distance between two phones by estimating the traveling time of audio signal from one phone to the other as the speed of sound is known. The preliminary results of ranging demonstrate that our algorithm could achieve high accuracy, and stable and reliable results for real time smartphone-based indoor ranging
Acoustic Integrity Codes: Secure Device Pairing Using Short-Range Acoustic Communication
Secure Device Pairing (SDP) relies on an out-of-band channel to authenticate
devices. This requires a common hardware interface, which limits the use of
existing SDP systems. We propose to use short-range acoustic communication for
the initial pairing. Audio hardware is commonly available on existing
off-the-shelf devices and can be accessed from user space without requiring
firmware or hardware modifications. We improve upon previous approaches by
designing Acoustic Integrity Codes (AICs): a modulation scheme that provides
message authentication on the acoustic physical layer. We analyze their
security and demonstrate that we can defend against signal cancellation attacks
by designing signals with low autocorrelation. Our system can detect
overshadowing attacks using a ternary decision function with a threshold. In
our evaluation of this SDP scheme's security and robustness, we achieve a bit
error ratio below 0.1% for a net bit rate of 100 bps with a signal-to-noise
ratio (SNR) of 14 dB. Using our open-source proof-of-concept implementation on
Android smartphones, we demonstrate pairing between different smartphone
models.Comment: 11 pages, 11 figures. Published at ACM WiSec 2020 (13th ACM
Conference on Security and Privacy in Wireless and Mobile Networks). Updated
reference
Deep Room Recognition Using Inaudible Echos
Recent years have seen the increasing need of location awareness by mobile
applications. This paper presents a room-level indoor localization approach
based on the measured room's echos in response to a two-millisecond single-tone
inaudible chirp emitted by a smartphone's loudspeaker. Different from other
acoustics-based room recognition systems that record full-spectrum audio for up
to ten seconds, our approach records audio in a narrow inaudible band for 0.1
seconds only to preserve the user's privacy. However, the short-time and
narrowband audio signal carries limited information about the room's
characteristics, presenting challenges to accurate room recognition. This paper
applies deep learning to effectively capture the subtle fingerprints in the
rooms' acoustic responses. Our extensive experiments show that a two-layer
convolutional neural network fed with the spectrogram of the inaudible echos
achieve the best performance, compared with alternative designs using other raw
data formats and deep models. Based on this result, we design a RoomRecognize
cloud service and its mobile client library that enable the mobile application
developers to readily implement the room recognition functionality without
resorting to any existing infrastructures and add-on hardware.
Extensive evaluation shows that RoomRecognize achieves 99.7%, 97.7%, 99%, and
89% accuracy in differentiating 22 and 50 residential/office rooms, 19 spots in
a quiet museum, and 15 spots in a crowded museum, respectively. Compared with
the state-of-the-art approaches based on support vector machine, RoomRecognize
significantly improves the Pareto frontier of recognition accuracy versus
robustness against interfering sounds (e.g., ambient music).Comment: 29 page
u-BeepBeep: Low Energy Acoustic Ranging on Mobile Devices
We present u-BeepBeep: a low energy acoustic ranging ser-
vice for mobile phones. -BeepBeep combines the efficacy of the basic BeepBeep ranging mechanism with a light-weight cross-correlation mechanism based on sparse approximation
PIANO: Proximity-based User Authentication on Voice-Powered Internet-of-Things Devices
Voice is envisioned to be a popular way for humans to interact with
Internet-of-Things (IoT) devices. We propose a proximity-based user
authentication method (called PIANO) for access control on such voice-powered
IoT devices. PIANO leverages the built-in speaker, microphone, and Bluetooth
that voice-powered IoT devices often already have. Specifically, we assume that
a user carries a personal voice-powered device (e.g., smartphone, smartwatch,
or smartglass), which serves as the user's identity. When another voice-powered
IoT device of the user requires authentication, PIANO estimates the distance
between the two devices by playing and detecting certain acoustic signals;
PIANO grants access if the estimated distance is no larger than a user-selected
threshold. We implemented a proof-of-concept prototype of PIANO. Through
theoretical and empirical evaluations, we find that PIANO is secure, reliable,
personalizable, and efficient.Comment: To appear in ICDCS'1
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