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ENDORSE: Preliminary work on the
Privacy Rules Definition Language




Presented by Mark McLaughlin
Motivation for PRDL

• Provide a domain specific language to
  facilitate the creation of rules to address
  the main areas of concern in ENDORSE:
  – Making privacy terms transparent to the
    user/customer and providing better
    guarantees on data protection.

  – Providing a powerful tool to aid organizations
    holding personal data to comply with data
    protection & privacy law and regulations.
Challenges for PRDL

• “[identifying] .. relevant legal requirements from
  policies, laws and guidance documents and
  aligning these requirements with software
  specifications to maintain a defensible position
  in a court of law” - Travis D. Breaux

• Identifying the best method of evaluating privacy
  & data protection rules in the context of
  ENDORSE and the organisational system(s) in
  which ENDORSE deployments will reside.
8/2/2011                                               3
Rule Examples

• Rule 1: Legal Dept may delete data
  [Permission]
• Rule 2: Company must store data for 10
  years after contract or claim closure date.
  [Obligation]
• Rule 3: Company may store data if
  consent for marketing exists. [Conditional
  permission]

8/2/2011                                        4
Rules choices

• What do the rules do? E.g. reasoning versus
  access control:
      – Forward/backward chaining rules engine v XACML
• Expert system v policy translation.
• Gathering stakeholder requirements in terms of
  “types of rules” to see what we need to be able
  to deal with.
• Look at the kind of systems our rules will
  ‘respond to’ or ‘control’.

8/2/2011                                                 5
Current Meta Rule Model




8/2/2011                             6
PRDL Progress




8/2/2011                   7
Thank you.

           Questions & Discussion.




8/2/2011                             8

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Endorse cluster meeting

  • 1. ENDORSE: Preliminary work on the Privacy Rules Definition Language Presented by Mark McLaughlin
  • 2. Motivation for PRDL • Provide a domain specific language to facilitate the creation of rules to address the main areas of concern in ENDORSE: – Making privacy terms transparent to the user/customer and providing better guarantees on data protection. – Providing a powerful tool to aid organizations holding personal data to comply with data protection & privacy law and regulations.
  • 3. Challenges for PRDL • “[identifying] .. relevant legal requirements from policies, laws and guidance documents and aligning these requirements with software specifications to maintain a defensible position in a court of law” - Travis D. Breaux • Identifying the best method of evaluating privacy & data protection rules in the context of ENDORSE and the organisational system(s) in which ENDORSE deployments will reside. 8/2/2011 3
  • 4. Rule Examples • Rule 1: Legal Dept may delete data [Permission] • Rule 2: Company must store data for 10 years after contract or claim closure date. [Obligation] • Rule 3: Company may store data if consent for marketing exists. [Conditional permission] 8/2/2011 4
  • 5. Rules choices • What do the rules do? E.g. reasoning versus access control: – Forward/backward chaining rules engine v XACML • Expert system v policy translation. • Gathering stakeholder requirements in terms of “types of rules” to see what we need to be able to deal with. • Look at the kind of systems our rules will ‘respond to’ or ‘control’. 8/2/2011 5
  • 6. Current Meta Rule Model 8/2/2011 6
  • 8. Thank you. Questions & Discussion. 8/2/2011 8