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Privacy-­‐by-­‐Design Framework	
  for	
  Assessing
Internet	
  of	
  Things	
  Applications	
  and	
  Platforms
Charith	
  Perera,	
  Ciaran	
  McCormick,	
  Arosha	
  K.	
  Bandara,	
  Blaine	
  Price,	
  Bashar	
  Nuseibeh
The	
  6th	
  International	
  Conference	
  on	
  the	
  Internet	
  of	
  Things	
  (IoT	
  2016)	
  November	
  7–9,	
  2016	
  in	
  Stuttgart,	
  Germany.
Internet	
  of	
  Things
• The	
  Internet	
  of	
  Things	
  (IoT)	
  is	
  “…the	
  network	
  of	
  physical	
  objects—
devices,	
  vehicles,	
  buildings	
  and	
  other	
  items—embedded	
  with	
  electronics,	
  
software,	
  sensors,	
  and	
  network	
  connectivity	
  that	
  enables	
  these	
  objects	
  to	
  
collect	
  and	
  exchange	
  data…”#
• By	
  2020,	
  there	
  will	
  be	
  50	
  to	
  100	
  billion	
  devices	
  (i.e.	
  things,	
  sensors,	
  smart	
  
objects)	
  connected	
  to	
  the	
  Internet*
#	
  International	
  Telecommunication	
  Union,	
  Internet	
  of	
  Things	
  Global	
  Standards	
  Initiative,	
  2015,	
  http://www.itu.int/en/ITU-­‐T/gsi/iot/Pages/default.aspx
*	
  International	
  Data	
  Corporation	
  (IDC)	
  Corporate	
  USA,	
  “Worldwide	
  smart	
  connected	
  device	
  shipments,”	
  March	
  2012,	
  http://www.idc.com/getdoc.jsp?containerId=prUS23398412
Application	
  Development
Desktop	
  Application
Mobile	
  Application
Web	
  Application	
  Application
• Processing	
  happens	
  locally
• UI	
  sits	
  locally
• Processing	
  happens	
  locally
complemented	
  by	
  cloud	
  
resources
• UI	
  sits	
  locally
• Processing	
  happens	
  remotely
• UI	
  sits	
  locally
Internet	
  of	
  Things	
  Application	
  Development
BeagleBone
Waspmote
Raspberry PiArdunio
Gadgeteer
Dragonboard 410C
• NO Operating System
• Less Powerful
• OS Driven
• More Powerful
Cloud Computing
• Unlimited Computational
Resources*
Todays	
  IoT	
  Development	
  Market
Hardware Software
Privacy-­‐by-­‐Design
• IoT	
  applications	
  are	
  complex	
  by	
  nature	
  as	
  
they	
  involve	
  both	
  software	
  and	
  hardware	
  as	
  
well	
  as	
  many	
  different	
  types	
  of	
  	
  computational	
  
devices	
  (e.g.,	
  sensors,	
  gateways,	
  cloud)
• Privacy	
  is	
  a	
  significant	
  problem	
  in	
  IoT	
  
applications	
  because	
  they	
  handle	
  data	
  that	
  
can	
  be	
  used	
  to	
  derive	
  very	
  sensitive	
  personal	
  
information
Why	
  hasn’t	
  privacy	
  been	
  a	
  priority?
• IoT	
  systems	
  (applications,	
  service,	
  platforms)	
  are	
  still	
  new;	
  Not	
  mature	
  enough
• Most	
  IoT	
  platforms	
  follow	
  the	
  philosophy	
  “You	
  feed	
  your	
  data	
  to	
  our	
  platform,	
  we	
  
do	
  the	
  processing	
  and	
  give	
  you	
  back	
  the	
  results”
• Current	
  IoT	
  platform	
  providers	
  assume,	
  anyone	
  who	
  uses	
  their	
  platform	
  has	
  the	
  full	
  
ownership	
  of	
  the	
  data	
  they	
  feed.	
  (In	
  reality	
  this	
  is	
  not	
  the	
  case	
  always)
• Therefore,	
  privacy	
  is	
  not	
  a	
  major	
  concern	
  for	
  IoT	
  platform	
  providers.
Our	
  Motivation	
  and	
  Proposed	
  solution
• There	
  isn’t	
  any	
  process/methodology/framework	
  to	
  help	
  software	
  architects	
  in	
  
assessing	
  and	
  designing	
  IoT	
  applications
• Existing	
  frameworks	
  are	
  not	
  prescriptive	
  enough	
  to	
  follow	
  by	
  an	
  engineer
(We	
  discuss	
  them	
  few	
  slides	
  later)
• Recent	
  Security	
  and	
  Privacy	
  Violations:	
  HACKING	
  IoT:	
  A	
  Case	
  Study	
  on	
  Baby	
  Monitor	
  
Exposures	
  and	
  Vulnerabilities#
• Therefore,	
  we	
  wanted	
  to	
  build	
  	
  a	
  Privacy-­‐by-­‐design	
  framework	
  that	
  can	
  guide	
  
software	
  architects	
  in	
  assessing	
  IoT	
  application.
#	
  https://www.rapid7.com/docs/Hacking-­‐IoT-­‐A-­‐Case-­‐Study-­‐on-­‐Baby-­‐Monitor-­‐Exposures-­‐and-­‐Vulnerabilities.pdf
BUT	
  IT	
  IS	
  NOT	
  ….
• Guidelines	
  SHOULD	
  NOT	
  be	
  used	
  to	
  compare	
  
different	
  IoT	
  application	
  or	
  platforms.	
  
• The	
  primary	
  reason	
  is	
  that	
  each	
  IoT	
  application	
  or	
  
platforms	
  is	
  designed	
  to	
  serve	
  a	
  specific	
  purpose	
  
or	
  category	
  of	
  application.
Focus:	
  Enterprise	
  middleware	
  platform	
  for	
  
Smart	
  Cities	
  and	
  Businesses
Focus:	
  Smart	
  Home	
  Automation
What	
  is	
  out	
  there	
  ?	
  (Literature)
Privacy	
  by	
  Design	
  	
  Foundational	
  Principles	
  -­‐ Ann	
  Cavoukian*
1) Proactive	
  not	
  reactive;	
  preventative	
  not	
  remedial
2) Privacy	
  as	
  the	
  default	
  setting
3) Privacy	
  embedded	
  into	
  design
4) Full	
  functionality	
  positive-­‐sum,	
  not	
  zero-­‐sum
5) End-­‐to-­‐end	
  security-­‐full	
  life-­‐cycle	
  protection
6) Visibility	
  and	
  transparency-­‐ keep	
  it	
  open
7) Respect	
  for	
  user	
  privacy,	
  keep	
  it	
  user-­‐centric
*A.	
  Cavoukian,	
  “Resolution	
  on	
  privacy	
  by	
  design,”	
  in	
  32nd	
  International	
  Conference	
  of	
  Data	
  Protection	
  and	
  Privacy	
  Commissioners,	
  2010.
What	
  is	
  out	
  there	
  ?	
  (Literature)
LINDDUN	
  – Deng	
  et	
  al.*
*M.	
  Deng,	
  K.	
  Wuyts,	
  R.	
  Scandariato,	
  B.	
  Preneel,	
  and	
  W.	
  Joosen,	
  “A	
  privacy	
  threat	
  analysis	
  framework:	
  supporting	
  the	
  elicitation	
  and	
  fulfillment of	
  privacy	
  requirements,”	
  
Requirements	
  Engineering,	
  vol.	
  16,	
  no.	
  1,	
  pp.	
  3–32,	
  2011.
This	
  is	
  a	
  privacy	
  threat	
  analysis	
  framework	
  that	
  uses	
  data	
  flow	
  diagrams	
  (DFD)	
  to	
  identify	
  privacy	
  threats.	
  
1) Define	
  the	
  DFD
2) Map	
  privacy	
  threats	
  to	
  DFD	
  elements	
  
3) Identify	
  threat	
  scenarios
4) Prioritize	
  threats
5) Elicit	
  mitigation	
  strategies
6) Select	
  corresponding	
  PETS
What	
  is	
  out	
  there	
  ?	
  (Literature)
*J.-­‐H.	
  Hoepman,	
  "Privacy	
  Design	
  Strategies,"	
  in	
  ICT	
  Systems	
  Security	
  and	
  Privacy	
  Protection,	
  vol.	
  428,	
  N.	
  Cuppens-­‐Boulahia,	
  F.	
  Cuppens,	
  S.	
  Jajodia,	
  A.	
  Abou El	
  Kalam and	
  T.	
  Sans,	
  
Eds.,	
  Springer	
  Berlin	
  Heidelberg,	
  2014,	
  pp.	
  446-­‐459.
Privacy	
  Design	
  Strategies	
  –Hoepman*
1) Minimize
2) Hide
3) Separate
4) Aggregate
5) Inform
6) Control
7) Enforce
8) Demonstrate
• We	
  determined	
  that	
  Hoepman’s	
   is	
  the	
  most	
  appropriate	
  starting	
  point	
  for	
  
developing	
  a	
  more	
  detailed	
  privacy-­‐by-­‐design
• Primarily	
  because	
  this	
  framework	
  already	
  focuses	
  on	
  the	
  architectural	
  aspects	
  of	
  
privacy	
  design
IoT	
  Data	
  Flow	
  View
CDA
DPP
DPADS
DD
CDA
DPP
DPADS
DD
CDA
DPP
DPADS
DD
CDA
DPP
DPA
DS
DD
Consent	
  and	
  
Data	
  Acquisition
Data	
  Pre-­‐Processing
Data	
  Processing	
  and	
  
Analysis
Data	
  Storage
Data	
  Dissemination
Privacy	
  By	
  Design	
  Guidelines
1) Minimise data acquisition
2) Minimise number of data sources
3) Minimise raw data intake
4) Minimize knowledge discovery
5) Minimize data storage
6) Minimize data retention period
7) Hidden data routing
8) Data anonymization
9) Encrypted data communication
10) Encrypted data processing
11) Encrypted data storage
12) Reduce data granularity
13) Query answering
14) Repeated query blocking
15) Distributed data processing
16) Distributed data storage
17) Knowledge discovery based aggregation
18) Geography based aggregation
19) Chain aggregation
20) Time-Period based aggregation
21) Category based aggregation
22) Information Disclosure
23) Control
24) Logging
25) Auditing
26) Open Source
27) Data Flow Diagrams (DFD)
28) Certification
29) Standardization
30) Compliance with Policy, Law, Regulations
MINIMISEHIDESEPARATE
AGGREGATIONDEMONSTRATE
INFORM
CONTROL	
  
/	
  ENFORCE
Evaluation	
  of	
  Privacy	
  Capabilities:	
  Methodology
• Step	
  1:	
  Identify	
  how	
  data	
  flows	
  in	
  the	
  existing	
  application	
  or	
  platform
• Step	
  2:	
  Build	
  a	
  table	
  for	
  each	
  node	
  where	
  columns	
  represent	
  data	
  life	
  
cycle	
  phases	
  and	
  rows	
  represent	
  each	
  privacy-­‐by-­‐design	
  guideline.
• Step	
  3:	
  Depending	
  on	
  the	
  level	
  of	
  detail	
  which	
  software	
  architects	
  wish	
  to	
  
explore,	
  they	
  can	
  either	
  use	
  
(1)	
  a	
  summarised	
  colour	
  coding	
  base	
  scheme
(2)	
  a	
  notes	
  based	
  scheme
Evaluation	
  of	
  Privacy	
  Capabilities:	
  Methodology
Platforms	
  We	
  Assessed
http://www.eclipse.org/smarthome/ https://github.com/OpenIotOrg/openiot
• Focus:	
  Enterprise	
  middleware	
  platform	
  
for	
  Smart	
  Cities	
  and	
  Businesses
• Middleware	
  infrastructure	
  supports	
  
flexible	
  configuration	
  and	
  deployment	
  of	
  
algorithms	
  for	
  collecting,	
  and	
  filtering	
  
information	
  streams	
  stemming	
  from	
  
internet	
  connected	
  objects
• Focus:	
  Smart	
  Home	
  Automation
• Platform	
  for	
  integrating	
  different	
  home	
  
automation	
  systems	
  and	
  technologies	
  into	
  
one	
  single	
  solution	
  that	
  allows	
  over-­‐
arching	
  automation	
  rules	
  and	
  uniform	
  
user	
  interfaces
Results
Research	
  Directions
• Can	
  1)	
  Novice	
  2)	
  Experience	
  
Software	
  architects	
  assess	
  a	
  given	
  platform	
  using	
  the	
  proposed	
  guidelines	
  
consistently?	
  If	
  there	
  are	
  variation,	
  why?
• Given	
  a	
  case	
  study,	
  can	
  privacy	
  guidelines	
  guide	
  1)	
  Novice	
  2)	
  Experience
Towards	
  a better privacy-­‐aware	
  IoT	
  applications
Evaluation
Future	
  work
• Privacy	
  Tactics	
  -­‐ Tactics	
  are	
  design	
  decisions	
  that	
  improve	
  individual	
  quality	
  
attribute	
  (e.g.	
  Privacy)	
  concerns.	
  [Basic	
  building	
  blocks]
• Privacy	
  Patterns	
  -­‐ Patterns describe	
  the	
  high-­‐level	
  structure	
  and	
  behaviour	
  of	
  
software	
  systems	
  as	
  the	
  solution	
  to	
  multiple	
  system	
  requirements
[Complex	
  Compositions]
Thank	
  You

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IOT-2016 7-9 Septermber, 2016, Stuttgart, Germany

  • 1. Privacy-­‐by-­‐Design Framework  for  Assessing Internet  of  Things  Applications  and  Platforms Charith  Perera,  Ciaran  McCormick,  Arosha  K.  Bandara,  Blaine  Price,  Bashar  Nuseibeh The  6th  International  Conference  on  the  Internet  of  Things  (IoT  2016)  November  7–9,  2016  in  Stuttgart,  Germany.
  • 2. Internet  of  Things • The  Internet  of  Things  (IoT)  is  “…the  network  of  physical  objects— devices,  vehicles,  buildings  and  other  items—embedded  with  electronics,   software,  sensors,  and  network  connectivity  that  enables  these  objects  to   collect  and  exchange  data…”# • By  2020,  there  will  be  50  to  100  billion  devices  (i.e.  things,  sensors,  smart   objects)  connected  to  the  Internet* #  International  Telecommunication  Union,  Internet  of  Things  Global  Standards  Initiative,  2015,  http://www.itu.int/en/ITU-­‐T/gsi/iot/Pages/default.aspx *  International  Data  Corporation  (IDC)  Corporate  USA,  “Worldwide  smart  connected  device  shipments,”  March  2012,  http://www.idc.com/getdoc.jsp?containerId=prUS23398412
  • 3. Application  Development Desktop  Application Mobile  Application Web  Application  Application • Processing  happens  locally • UI  sits  locally • Processing  happens  locally complemented  by  cloud   resources • UI  sits  locally • Processing  happens  remotely • UI  sits  locally
  • 4. Internet  of  Things  Application  Development BeagleBone Waspmote Raspberry PiArdunio Gadgeteer Dragonboard 410C • NO Operating System • Less Powerful • OS Driven • More Powerful Cloud Computing • Unlimited Computational Resources*
  • 5. Todays  IoT  Development  Market Hardware Software
  • 6. Privacy-­‐by-­‐Design • IoT  applications  are  complex  by  nature  as   they  involve  both  software  and  hardware  as   well  as  many  different  types  of    computational   devices  (e.g.,  sensors,  gateways,  cloud) • Privacy  is  a  significant  problem  in  IoT   applications  because  they  handle  data  that   can  be  used  to  derive  very  sensitive  personal   information
  • 7. Why  hasn’t  privacy  been  a  priority? • IoT  systems  (applications,  service,  platforms)  are  still  new;  Not  mature  enough • Most  IoT  platforms  follow  the  philosophy  “You  feed  your  data  to  our  platform,  we   do  the  processing  and  give  you  back  the  results” • Current  IoT  platform  providers  assume,  anyone  who  uses  their  platform  has  the  full   ownership  of  the  data  they  feed.  (In  reality  this  is  not  the  case  always) • Therefore,  privacy  is  not  a  major  concern  for  IoT  platform  providers.
  • 8. Our  Motivation  and  Proposed  solution • There  isn’t  any  process/methodology/framework  to  help  software  architects  in   assessing  and  designing  IoT  applications • Existing  frameworks  are  not  prescriptive  enough  to  follow  by  an  engineer (We  discuss  them  few  slides  later) • Recent  Security  and  Privacy  Violations:  HACKING  IoT:  A  Case  Study  on  Baby  Monitor   Exposures  and  Vulnerabilities# • Therefore,  we  wanted  to  build    a  Privacy-­‐by-­‐design  framework  that  can  guide   software  architects  in  assessing  IoT  application. #  https://www.rapid7.com/docs/Hacking-­‐IoT-­‐A-­‐Case-­‐Study-­‐on-­‐Baby-­‐Monitor-­‐Exposures-­‐and-­‐Vulnerabilities.pdf
  • 9. BUT  IT  IS  NOT  …. • Guidelines  SHOULD  NOT  be  used  to  compare   different  IoT  application  or  platforms.   • The  primary  reason  is  that  each  IoT  application  or   platforms  is  designed  to  serve  a  specific  purpose   or  category  of  application. Focus:  Enterprise  middleware  platform  for   Smart  Cities  and  Businesses Focus:  Smart  Home  Automation
  • 10. What  is  out  there  ?  (Literature) Privacy  by  Design    Foundational  Principles  -­‐ Ann  Cavoukian* 1) Proactive  not  reactive;  preventative  not  remedial 2) Privacy  as  the  default  setting 3) Privacy  embedded  into  design 4) Full  functionality  positive-­‐sum,  not  zero-­‐sum 5) End-­‐to-­‐end  security-­‐full  life-­‐cycle  protection 6) Visibility  and  transparency-­‐ keep  it  open 7) Respect  for  user  privacy,  keep  it  user-­‐centric *A.  Cavoukian,  “Resolution  on  privacy  by  design,”  in  32nd  International  Conference  of  Data  Protection  and  Privacy  Commissioners,  2010.
  • 11. What  is  out  there  ?  (Literature) LINDDUN  – Deng  et  al.* *M.  Deng,  K.  Wuyts,  R.  Scandariato,  B.  Preneel,  and  W.  Joosen,  “A  privacy  threat  analysis  framework:  supporting  the  elicitation  and  fulfillment of  privacy  requirements,”   Requirements  Engineering,  vol.  16,  no.  1,  pp.  3–32,  2011. This  is  a  privacy  threat  analysis  framework  that  uses  data  flow  diagrams  (DFD)  to  identify  privacy  threats.   1) Define  the  DFD 2) Map  privacy  threats  to  DFD  elements   3) Identify  threat  scenarios 4) Prioritize  threats 5) Elicit  mitigation  strategies 6) Select  corresponding  PETS
  • 12. What  is  out  there  ?  (Literature) *J.-­‐H.  Hoepman,  "Privacy  Design  Strategies,"  in  ICT  Systems  Security  and  Privacy  Protection,  vol.  428,  N.  Cuppens-­‐Boulahia,  F.  Cuppens,  S.  Jajodia,  A.  Abou El  Kalam and  T.  Sans,   Eds.,  Springer  Berlin  Heidelberg,  2014,  pp.  446-­‐459. Privacy  Design  Strategies  –Hoepman* 1) Minimize 2) Hide 3) Separate 4) Aggregate 5) Inform 6) Control 7) Enforce 8) Demonstrate • We  determined  that  Hoepman’s   is  the  most  appropriate  starting  point  for   developing  a  more  detailed  privacy-­‐by-­‐design • Primarily  because  this  framework  already  focuses  on  the  architectural  aspects  of   privacy  design
  • 13. IoT  Data  Flow  View CDA DPP DPADS DD CDA DPP DPADS DD CDA DPP DPADS DD CDA DPP DPA DS DD Consent  and   Data  Acquisition Data  Pre-­‐Processing Data  Processing  and   Analysis Data  Storage Data  Dissemination
  • 14. Privacy  By  Design  Guidelines 1) Minimise data acquisition 2) Minimise number of data sources 3) Minimise raw data intake 4) Minimize knowledge discovery 5) Minimize data storage 6) Minimize data retention period 7) Hidden data routing 8) Data anonymization 9) Encrypted data communication 10) Encrypted data processing 11) Encrypted data storage 12) Reduce data granularity 13) Query answering 14) Repeated query blocking 15) Distributed data processing 16) Distributed data storage 17) Knowledge discovery based aggregation 18) Geography based aggregation 19) Chain aggregation 20) Time-Period based aggregation 21) Category based aggregation 22) Information Disclosure 23) Control 24) Logging 25) Auditing 26) Open Source 27) Data Flow Diagrams (DFD) 28) Certification 29) Standardization 30) Compliance with Policy, Law, Regulations MINIMISEHIDESEPARATE AGGREGATIONDEMONSTRATE INFORM CONTROL   /  ENFORCE
  • 15. Evaluation  of  Privacy  Capabilities:  Methodology • Step  1:  Identify  how  data  flows  in  the  existing  application  or  platform • Step  2:  Build  a  table  for  each  node  where  columns  represent  data  life   cycle  phases  and  rows  represent  each  privacy-­‐by-­‐design  guideline. • Step  3:  Depending  on  the  level  of  detail  which  software  architects  wish  to   explore,  they  can  either  use   (1)  a  summarised  colour  coding  base  scheme (2)  a  notes  based  scheme
  • 16. Evaluation  of  Privacy  Capabilities:  Methodology
  • 17. Platforms  We  Assessed http://www.eclipse.org/smarthome/ https://github.com/OpenIotOrg/openiot • Focus:  Enterprise  middleware  platform   for  Smart  Cities  and  Businesses • Middleware  infrastructure  supports   flexible  configuration  and  deployment  of   algorithms  for  collecting,  and  filtering   information  streams  stemming  from   internet  connected  objects • Focus:  Smart  Home  Automation • Platform  for  integrating  different  home   automation  systems  and  technologies  into   one  single  solution  that  allows  over-­‐ arching  automation  rules  and  uniform   user  interfaces
  • 19. Research  Directions • Can  1)  Novice  2)  Experience   Software  architects  assess  a  given  platform  using  the  proposed  guidelines   consistently?  If  there  are  variation,  why? • Given  a  case  study,  can  privacy  guidelines  guide  1)  Novice  2)  Experience Towards  a better privacy-­‐aware  IoT  applications Evaluation Future  work • Privacy  Tactics  -­‐ Tactics  are  design  decisions  that  improve  individual  quality   attribute  (e.g.  Privacy)  concerns.  [Basic  building  blocks] • Privacy  Patterns  -­‐ Patterns describe  the  high-­‐level  structure  and  behaviour  of   software  systems  as  the  solution  to  multiple  system  requirements [Complex  Compositions]