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Privacy	  for	  2020	  
•  h"p://   v=2HHEQuspi4o	  
Ubiquitous/Pervasive	  CompuAng	  •  Smartphone	     –  5G	  –	  high	  bandwidth	  (operator	  specific)	     –  Individua...
Data	  Environment	  •  Data	  types	      –  Network	  specific	      –  ApplicaAon/service	  specific	  •  Same	  data	  u...
Stakeholders	  •  Everyone/thing	  involved	  –	  many	  perspecAves,	     many	  players,	  many	  moAvaAons,	  many	    ...
Paradigm	  Shic	  (?)	  •  Data	  closer	  to	  the	  users	      –  DecentralisaAon	  •  Individuals	  (more)	  in	  char...
Future	  healthcare	  •  Possibility	  to	  collect	  rich	  data	         –  Vital	  signs,	  environmental,	  event	  de...
Healthcare	  scenario	  •  Bob’s	  everyday	  life	  is	  highly	  digital	      –  Smart	  home/city	      –  Smartphone	...
Technical	  ConsideraAons	  •  SpecificaAon	  of	  preferences	      –  Bob	  only	  wants	  his	  data	  used	  in	  certa...
Economic	  ConsideraAons	  •  IncenAves	  for	  sharing	     –  Bob	  ‘trusts’	  his	  doctor,	  but	  maybe	  not	  his	 ...
Social	  ConsideraAons 	  	  •  Awareness	     –  Newer	  generaAons	  more	  privacy	  aware	         •  Different	  value...
Legal	  ConsideraAons	  •  Blurring	  of	  data	  controller	  and	  data	  subjects	  •  The	  role	  of	  individuals	  ...
Generally…	  •  In	  2020:	  ‘exisAng’	  concerns,	  new	  concerns	     –  Individuals	  more	  involved	  (no	  longer	 ...
More	  funding	  
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Privacy 2020 (Participants) EINS summer school


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Network of Excellence Internet Science Summer School. The theme of the summer school is "Internet Privacy and Identity, Trust and Reputation Mechanisms".
More information:

Tulio de Souza
Kinfemicheal Yilma Desta
Maria Lambrou
Wonjae Lee
Gaia Leli
Kai Samelin
Jat Singh

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Privacy 2020 (Participants) EINS summer school

  1. 1. Privacy  for  2020  
  2. 2. •  h"p:// v=2HHEQuspi4o  
  3. 3. Ubiquitous/Pervasive  CompuAng  •  Smartphone   –  5G  –  high  bandwidth  (operator  specific)   –  Individuals  ‘personal  hub’  •  Technology  is  everywhere,  always  on   –  Live  vs.  stored  informaAon   –  Perpetual  persistence  •  Advanced  data  mining/inferencing/predicAve   capabiliAes  •  Every  person,  mulAple  devices,  services    
  4. 4. Data  Environment  •  Data  types   –  Network  specific   –  ApplicaAon/service  specific  •  Same  data  useful  in  a  number  different  contexts   (environmental)   –  CollecAon  (may  be)  context  free  •  Direct  connecAons  –  not  just  cloud  •  ‘Live  data’  •  Lots  of  data,  lots  of  sources/sinks   =>  LOTS  OF  POSSIBLE  (MIS)USES   –  Governance  becomes  more  complex  in  2020    
  5. 5. Stakeholders  •  Everyone/thing  involved  –  many  perspecAves,   many  players,  many  moAvaAons,  many   objecAves   –  All  can  (potenAally)  collect,  process,  consume   –  Different  to  standard:  govt,  company,  user…  •  (Appropriate)  InteracAons  depend  on  context   –  Today  –  central  (cloud?)  services   •  Historical  request-­‐based   –  Push-­‐based  informaAon  &  ad-­‐hoc  connecAons   •  MediaAon/enforcement  
  6. 6. Paradigm  Shic  (?)  •  Data  closer  to  the  users   –  DecentralisaAon  •  Individuals  (more)  in  charge   –  Data  release,  coordinaAon  •  Individuals  do  more  than  just  ‘use’      •  What  does  this  mean  for  data  privacy?   –  Norms:  Legal,  social,  economic,  technical   –  Healthcare  perspecAve  
  7. 7. Future  healthcare  •  Possibility  to  collect  rich  data   –  Vital  signs,  environmental,  event  detecAon  (falls)  •  Such  data  is  relevant  to  many  applicaAons   –  E.g.  heart  rate  data  (ECG)   •  Diagnosis  (database,  status  updates)   •  PaAent-­‐feedback  (e.g.  exercise  monitoring)   •  Emergency  situaAons  •  Relevance  depends  on  context    
  8. 8. Healthcare  scenario  •  Bob’s  everyday  life  is  highly  digital   –  Smart  home/city   –  Smartphone  Gaia®  is  central  to  his  life   •  Many  applicaAons  manage  his  work,  social  acAvity,  …  •  Bob  has  heart  disease    •  Smartphone  Gaia®  collects  relevant  to  his  condiAon   –  Everyday  life,  vital  signs,  ...   –  Inferencing  capabiliAes  (e.g.  falls,  heart  a"acks)  •  Data  should  flow  to  relevant  parAes     –  Depends  on  CONTEXT   –  Doctor  (individual),  Doctor’s  Surgery,  Insurance   Company,  Family,  Health  Service  
  9. 9. Technical  ConsideraAons  •  SpecificaAon  of  preferences   –  Bob  only  wants  his  data  used  in  certain  ways   –  Is  this  feasible?   •  Management  of  work  data  is  different  to  his  social  data   •  Health  data  is  specific:  exercise,  diagnosis,  emergency  •  Systems  should  react  to  context   –  Doctor  cannot  access  Bob’s  live  datastreams,  EXCEPT  in  an   emergency  •  System  design  issues   –  Can’t  pre-­‐empt  every  use/datasource;     •  Bob’s  home  might  differ  to  his  neighbours   –  But  there  are  standards/models/templates   •  Usage  templates  for  heart  disease  paAents,  that  can  be  tweaked  
  10. 10. Economic  ConsideraAons  •  IncenAves  for  sharing   –  Bob  ‘trusts’  his  doctor,  but  maybe  not  his  gym  •  QuanAfying  (valuing)  privacy?   –  Insurance  company  valuaAon   •  Does  Bob  give  his  data  for  a  discounted  premium?   –  Bob  doesn’t  care  when  having  a  heart  a"ack…  •  Future  markets  for  privacy  protecAon?   –  Anonymous  medical  billing  services    
  11. 11. Social  ConsideraAons    •  Awareness   –  Newer  generaAons  more  privacy  aware   •  Different  values  of  different  generaAons?   •  Assist  the  elders?  Will  Bob’s  children  help  him  •  More  data,  more  actors,  more  complexity   –  How  can  Bob  cope?  •  Future  technology  has  more  potenAal  to   impact  privacy   –  Benefits  for  Bob,  his  family  (and  society…)  
  12. 12. Legal  ConsideraAons  •  Blurring  of  data  controller  and  data  subjects  •  The  role  of  individuals   –  Processing  can  be  done  by  other  individuals   •  Bob’s  wife?  Doctor?     –  Are  they  data  controllers?   –  NoAce,  consent?  •  ExecuAve  overrides   –  Access  Bob’s  data  in  medical  emergency?  NaAonal  security?  •  Power  of  authoriAes  to  set  privacy  standards   –  Currently  no,  but  drac  proposal  to  change  (DPR)   –  How  does  this  affect  individuals?  
  13. 13. Generally…  •  In  2020:  ‘exisAng’  concerns,  new  concerns   –  Individuals  more  involved  (no  longer  just  ‘users’)  •  Move  away  from  reacAon  to  tech   –  Involving  norms  in  the  design  process  •  R&D  efforts   –  Disciplinary  AND  mulAdisciplinary  •  Will  corporaAons  allow  decentralisaAon?  •  Visibility  of  privacy  issues   –  CollecAve  consciousness    
  14. 14. More  funding  
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