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Privacy	
  in	
  the	
  Cloud	
  
Nessrine	
  Omrani,	
  Serge	
  Pajak	
  
RITM,	
  University	
  Paris	
  Sud	
  
Privacy	
  in	
  the	
  Cloud	
  
•  Research	
   part	
   of	
   a	
   PAIP	
   project,	
   funded	
   by	
   the	
   Paris-­‐Saclay	
  
Idex,	
  InsFtute	
  for	
  a	
  Digital	
  Society	
  
•  Interdisciplinary	
   approach:	
   Economics,	
   Law	
   and	
   Computer	
  
Science	
  
Internship	
  at	
  the	
  department,	
  Simon	
  Bouget	
  ENS	
  Rennes	
  
The	
  Services	
  We	
  Focus	
  On:	
  
Automated	
  services	
  for	
  remote	
  storage	
  
and/or	
  synchroniza6on	
  between	
  devices	
  	
  
	
  
•  Highly	
  ‘privacy-­‐relevant’	
  since	
  personal	
  data	
  are	
  stored	
  
remotely	
  
•  Aimed	
  at	
  the	
  general	
  public	
  
–  Remember	
  the	
  privacy	
  paradox:	
  people	
  say	
  they	
  care	
  about	
  privacy,	
  
but	
  act	
  as	
  if	
  they	
  do	
  not	
  
–  Privacy	
  charters	
  are	
  difficult	
  to	
  read	
  (and	
  are	
  hardly	
  read	
  at	
  all…)	
  
•  Goal:	
  classificaFon	
  of	
  cloud	
  services,	
  related	
  to	
  performance	
  
Cloud	
  services	
  
•  50	
  services	
  
– Digital	
  giants:	
  Google,	
  MicrosoZ,	
  …	
  
– Leaders	
  of	
  the	
  industry:	
  Dropbox,	
  Box.com,	
  …	
  
– Open-­‐source	
  projects:	
  Cozy,	
  Sparkleshare,	
  …	
  
Two	
  steps…	
  
•  Working	
  tools:	
  Terms	
  of	
  use	
  and	
  Privacy	
  terms	
  
of	
  the	
  cloud	
  services’	
  websites	
  	
  
•  Two	
  steps:	
  
1.  Defining	
  the	
  classificaFon	
  grid	
  	
  
2.  RelaFng	
  the	
  variables	
  of	
  interest	
  to	
  measure	
  of	
  
performance	
  or	
  other	
  topic	
  
ClassificaFon	
  grid	
  
•  The	
  reading	
  grid	
  includes	
  the	
  following	
  variables:	
  
–  Intellectual	
  property:	
  Is	
  informaFon	
  about	
  I.P.	
  included?	
  	
  
–  Usage	
  permission:	
  The	
  clarity	
  of	
  the	
  usage	
  permission	
  
–  Data	
  access:	
  Who	
  have	
  access	
  to	
  the	
  data?	
  
–  Data	
  diffusion:	
  To	
  whom	
  the	
  data	
  is	
  disseminated?	
  
–  Data	
  backup:	
  Is	
  the	
  data	
  retenFon	
  period	
  indicated?	
  
–  Warranty:	
  InformaFon	
  about	
  the	
  warranty’s	
  degree	
  
–  Liability:	
   The	
   degree	
   of	
   liability	
   regarding	
   the	
   services’	
  
content	
  
–  Cookies:	
   Is	
   there	
   informaFon	
   about	
   the	
   existence	
   of	
  
cookies?	
  
ClassificaFon	
  grid:	
  
technical	
  part	
  
Source:	
  Simon	
  Bouget,	
  Jan.	
  2014	
  
The	
  aim	
  of	
  this	
  
classificaFon	
  effort	
  
•  Giving	
   a	
   becer	
   understanding	
   of	
   the	
   Privacy	
  
sedngs	
  of	
  the	
  cloud	
  services	
  
•  Trying	
   to	
   provide	
   a	
   ‘Privacy	
   dicFonnary’	
   for	
  
cloud	
  services’	
  users	
  

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Nessrine Omrani & Serge Pajak: Privacy in the cloud

  • 1. Privacy  in  the  Cloud   Nessrine  Omrani,  Serge  Pajak   RITM,  University  Paris  Sud  
  • 2. Privacy  in  the  Cloud   •  Research   part   of   a   PAIP   project,   funded   by   the   Paris-­‐Saclay   Idex,  InsFtute  for  a  Digital  Society   •  Interdisciplinary   approach:   Economics,   Law   and   Computer   Science   Internship  at  the  department,  Simon  Bouget  ENS  Rennes  
  • 3. The  Services  We  Focus  On:   Automated  services  for  remote  storage   and/or  synchroniza6on  between  devices       •  Highly  ‘privacy-­‐relevant’  since  personal  data  are  stored   remotely   •  Aimed  at  the  general  public   –  Remember  the  privacy  paradox:  people  say  they  care  about  privacy,   but  act  as  if  they  do  not   –  Privacy  charters  are  difficult  to  read  (and  are  hardly  read  at  all…)   •  Goal:  classificaFon  of  cloud  services,  related  to  performance  
  • 4. Cloud  services   •  50  services   – Digital  giants:  Google,  MicrosoZ,  …   – Leaders  of  the  industry:  Dropbox,  Box.com,  …   – Open-­‐source  projects:  Cozy,  Sparkleshare,  …  
  • 5. Two  steps…   •  Working  tools:  Terms  of  use  and  Privacy  terms   of  the  cloud  services’  websites     •  Two  steps:   1.  Defining  the  classificaFon  grid     2.  RelaFng  the  variables  of  interest  to  measure  of   performance  or  other  topic  
  • 6. ClassificaFon  grid   •  The  reading  grid  includes  the  following  variables:   –  Intellectual  property:  Is  informaFon  about  I.P.  included?     –  Usage  permission:  The  clarity  of  the  usage  permission   –  Data  access:  Who  have  access  to  the  data?   –  Data  diffusion:  To  whom  the  data  is  disseminated?   –  Data  backup:  Is  the  data  retenFon  period  indicated?   –  Warranty:  InformaFon  about  the  warranty’s  degree   –  Liability:   The   degree   of   liability   regarding   the   services’   content   –  Cookies:   Is   there   informaFon   about   the   existence   of   cookies?  
  • 7. ClassificaFon  grid:   technical  part   Source:  Simon  Bouget,  Jan.  2014  
  • 8. The  aim  of  this   classificaFon  effort   •  Giving   a   becer   understanding   of   the   Privacy   sedngs  of  the  cloud  services   •  Trying   to   provide   a   ‘Privacy   dicFonnary’   for   cloud  services’  users