Difference between revisions of "AFSecurity Seminar"

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| '''DATE:'''&nbsp; 30 August 2019<br />
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| '''DATE:'''&nbsp; 21 August 2019<br />
 
'''PLACE:'''&nbsp;  Kristan Nygaards Hall (Room 5370), IFI, UiO - OJD House . <br /><br />
 
'''PLACE:'''&nbsp;  Kristan Nygaards Hall (Room 5370), IFI, UiO - OJD House . <br /><br />
 
'''AGENDA:'''<br />
 
'''AGENDA:'''<br />
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* '''TALK:''' &nbsp;''Privacy Threat of Keystroke Profiling on the Web''<br />'''SPEAKER:''' ''Denis Migdal'' (ENSICAEN) &nbsp; <br />'''ABSTRACT:''' In a browser environment, Keystroke Dynamics (the way of typing on a keyboard) is an interesting biometric modality as it requires neither additional sensors (just your keyboard), nor additional actions from the user.  Keystroke Dynamics can easily be collected through a Web page to authenticate,  identify,  or profile visitors...  even without their knowledge and consent. Contrary  to  learning-based  Keystroke  Dynamics  (s.a.   based  on Deep  learning  or SVM), distance-based Keystroke Dynamics can be used with very few data.  However, it generally provides deceiving authentication and identification performances. In a first part, we will see how to improve such performances, and how Keystroke Dynamics can pose serious threats to users privacy, even with only few information. Fortunately, thanks to Keystroke Dynamics Anonymization Systems, it is possible to protect our Keystroke Dynamics, or at last to disturb identification and profiling systems. Several  Keystroke  Dynamics Anonymization  Systems  will  be  presented  in  the  second partas  well  as  some  recommendations  to build and  implement Keystroke  Dynamics Anonymization Systems. In a third part, I will present a multi-modal privacy-compliant authentication based, among other, on Keystroke Dynamics, as well as some schemes and uses cases.  Proof of authorship in an online collaborative document writing, or proof of identity on a Social Network constitute application of our proposed authentication. And if we still have time, the fourth part will be dedicated to synthetic generation of Keystroke Dynamics.  Usurpation of Keystroke Dynamics, Keystroke Dynamics dataset creation or augmentation, and better understanding of Keystroke Dynamics are goals of Keystroke Dynamics synthetic generation
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* '''TALK:''' &nbsp;''Privacy Threat of Keystroke Profiling on the Web''<br />'''SPEAKER:''' ''Denis Migdal'' (ENSICAEN) &nbsp; <br />'''ABSTRACT:''' In a browser environment, Keystroke Dynamics (the way of typing on a keyboard) is a biometric modality which can be used by any Web service to profile users. The collection of keystroke dynamics does not require any additional sensors and can be collected without the users' knowledge.  Keystroke Dynamics can be used to authenticate users, but also to profile otherwise anonymous web users, and thereby represents a privacy threat. This talk first discusses the performance of Keystroke Dynamics and how it poses a serious threat to users privacy. The talk then discusses several potential real-time methods for anonymization of Keystroke  Dynamics,  and gives some  recommendations  for building and  implementing Keystroke  Dynamics Anonymization Systems.  
16:00h Discussion<br />
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15:00h Discussion<br />
  
  
 
'''SPEAKER BIO''' <br/>
 
'''SPEAKER BIO''' <br/>
Denis Migdal is PhD student at ENSICAEN in Caen, France. His PhD research project focuses on privacy protection against user profiling which can exploit biometric keystroke dynamics of normal user activity on the Web.
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Denis Migdal is PhD student at ENSICAEN in Caen, France. His PhD research project focuses on biometric keystroke dynamics and methods to strengthen online trust and privacy.
 
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Revision as of 09:16, 16 August 2019

Privacy Threat of Keystroke Profiling on the Web

DATE:  21 August 2019

PLACE:  Kristan Nygaards Hall (Room 5370), IFI, UiO - OJD House .

AGENDA:
14:00h Welcom at UiO

14:15h Invited Talk:

Logo-ENSICAEN.png
  • TALK:  Privacy Threat of Keystroke Profiling on the Web
    SPEAKER: Denis Migdal (ENSICAEN)  
    ABSTRACT: In a browser environment, Keystroke Dynamics (the way of typing on a keyboard) is a biometric modality which can be used by any Web service to profile users. The collection of keystroke dynamics does not require any additional sensors and can be collected without the users' knowledge. Keystroke Dynamics can be used to authenticate users, but also to profile otherwise anonymous web users, and thereby represents a privacy threat. This talk first discusses the performance of Keystroke Dynamics and how it poses a serious threat to users privacy. The talk then discusses several potential real-time methods for anonymization of Keystroke Dynamics, and gives some recommendations for building and implementing Keystroke Dynamics Anonymization Systems.

15:00h Discussion


SPEAKER BIO
Denis Migdal is PhD student at ENSICAEN in Caen, France. His PhD research project focuses on biometric keystroke dynamics and methods to strengthen online trust and privacy.

AFSecurity-small.png AFSecurity is organised by the UiO Research Group on Information & Cyber Security Sec-uio-light-1000.png