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Secure authentication from ambient audio: Difference between revisions

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== Project Description ==
== Project Description ==
Indoor positioning still remains a challenging task since GPS does not work indoors and reliable.
In preliminary studies, fingerprints from ambient audio have been utilised to generate a secure key among devices without the necessitiy of a trusted third party
Furthermore, ubiquitously deployed alternatives are not available.  
([http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6112755 1], [http://link.springer.com/chapter/10.1007%2F978-3-642-30973-1_31 2], [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6246148 3]).
Recenty, localisation techniques based on radio frequency measurements have been proposed.


In this project, the student(s) will design and implement an indoor localisation system based on RF-signal strength fluctuation.  
In this implementation, similar recordings of ambient audio from mobile devices in proximity are utilised for the generation of a secure key.
We will provide USRP software defined radio devices and further required hardware equipment to design an accurate RF-based indoor localisation system.
An attacker that is farther away is not able to guess the same key with a recording of her own since the features in the ambient audio differ with location.
In the frame of the 2014 IPSN Indoor Localisation Competition [http://ipsn.acm.org/2014/content/pdf/IndoorLocation-CFC.pdf] the designed system can be tested under realistic conditions.
However, the robustness of the generated key is dependent on properties of ambient audio.  
A participation is highly appreciated and will be supported.
In previous studies, we experienced best pairing characteristics when devices are in an environment with a single loud audio source.
When environmental noise is, however, more ubiquitous and noisy, it is easier for an attacker to generate a key that is similar to that of the legitimate communication partners.
 
In this project we will develop a mechanism to adapt the parameter of the underlying approach to generate secure to changing environmental parameters.
 
 
[[File:AudioSynch.png]]


== Required Skills ==
== Required Skills ==
* Natural curiosity, high motivation and a good sense of creativity :)
* Natural curiosity, high motivation and a good sense of creativity :)
* Programming skills in Python will be required but can also be acquired in the course of the project
* Some basic understanding of machine learning techniques, audio-fingerprinting, error correction or fuzzy cryptograpy might be helpful but will also be acquired throughout the project (Since there are implementations already, none of these have to be done from scratch)
* Basic understanding of physical layer effects of wireless communication will be helpful
* Experience with audio processing might be helpful but is not mandatory
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