626 research outputs found
Fingerprinting Smart Devices Through Embedded Acoustic Components
The widespread use of smart devices gives rise to both security and privacy
concerns. Fingerprinting smart devices can assist in authenticating physical
devices, but it can also jeopardize privacy by allowing remote identification
without user awareness. We propose a novel fingerprinting approach that uses
the microphones and speakers of smart phones to uniquely identify an individual
device. During fabrication, subtle imperfections arise in device microphones
and speakers which induce anomalies in produced and received sounds. We exploit
this observation to fingerprint smart devices through playback and recording of
audio samples. We use audio-metric tools to analyze and explore different
acoustic features and analyze their ability to successfully fingerprint smart
devices. Our experiments show that it is even possible to fingerprint devices
that have the same vendor and model; we were able to accurately distinguish
over 93% of all recorded audio clips from 15 different units of the same model.
Our study identifies the prominent acoustic features capable of fingerprinting
devices with high success rate and examines the effect of background noise and
other variables on fingerprinting accuracy
Survey and Systematization of Secure Device Pairing
Secure Device Pairing (SDP) schemes have been developed to facilitate secure
communications among smart devices, both personal mobile devices and Internet
of Things (IoT) devices. Comparison and assessment of SDP schemes is
troublesome, because each scheme makes different assumptions about out-of-band
channels and adversary models, and are driven by their particular use-cases. A
conceptual model that facilitates meaningful comparison among SDP schemes is
missing. We provide such a model. In this article, we survey and analyze a wide
range of SDP schemes that are described in the literature, including a number
that have been adopted as standards. A system model and consistent terminology
for SDP schemes are built on the foundation of this survey, which are then used
to classify existing SDP schemes into a taxonomy that, for the first time,
enables their meaningful comparison and analysis.The existing SDP schemes are
analyzed using this model, revealing common systemic security weaknesses among
the surveyed SDP schemes that should become priority areas for future SDP
research, such as improving the integration of privacy requirements into the
design of SDP schemes. Our results allow SDP scheme designers to create schemes
that are more easily comparable with one another, and to assist the prevention
of persisting the weaknesses common to the current generation of SDP schemes.Comment: 34 pages, 5 figures, 3 tables, accepted at IEEE Communications
Surveys & Tutorials 2017 (Volume: PP, Issue: 99
Towards detection and control of civilian unmanned aerial vehicles
Considering the significant number of nonâmilitary unmanned aerial vehicles (UAVs) that can be purchased to operate in unregulated air space and the range of such devices, the potential for security and privacy problems to arise is significant. This can lead to consequent harm for critical infrastructure in the event of these UAVs being used for criminal or terrorist purposes. Further, if these devices are not being detected, there is a privacy problem to be addressed as well. In this paper we test a specific UAV, the Parrot AR Drone version 2, and present a forensic analysis of tests used to deactivate or render the device inoperative. It was found that these devices are open to attack, which means they could be controlled by a third party
Multibiometric security in wireless communication systems
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/08/2010.This thesis has aimed to explore an application of Multibiometrics to secured wireless communications. The medium of study for this purpose included Wi-Fi, 3G, and
WiMAX, over which simulations and experimental studies were carried out to assess the performance. In specific, restriction of access to authorized users only is provided by a technique referred to hereafter as multibiometric cryptosystem. In brief, the system is built upon a complete challenge/response methodology in order to obtain a high level of security on the basis of user identification by fingerprint and further confirmation by verification of the user through text-dependent speaker recognition.
First is the enrolment phase by which the database of watermarked fingerprints with
memorable texts along with the voice features, based on the same texts, is created by sending them to the server through wireless channel.
Later is the verification stage at which claimed users, ones who claim are genuine, are verified against the database, and it consists of five steps. Initially faced by the identification level, one is asked to first present oneâs fingerprint and a memorable word, former is watermarked into latter, in order for system to authenticate the fingerprint and verify the validity of it by retrieving the challenge for accepted user.
The following three steps then involve speaker recognition including the user
responding to the challenge by text-dependent voice, server authenticating the response, and finally server accepting/rejecting the user.
In order to implement fingerprint watermarking, i.e. incorporating the memorable word as a watermark message into the fingerprint image, an algorithm of five steps has been developed. The first three novel steps having to do with the fingerprint
image enhancement (CLAHE with 'Clip Limit', standard deviation analysis and
sliding neighborhood) have been followed with further two steps for embedding, and
extracting the watermark into the enhanced fingerprint image utilising Discrete
Wavelet Transform (DWT).
In the speaker recognition stage, the limitations of this technique in wireless
communication have been addressed by sending voice feature (cepstral coefficients)
instead of raw sample. This scheme is to reap the advantages of reducing the
transmission time and dependency of the data on communication channel, together
with no loss of packet. Finally, the obtained results have verified the claims
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