1. Jody Blanke and Janine Hiller August 7, 2017
Predictability As an Objective for Privacy Engineering and Risk Management
Jody Blanke and Janine Hiller August 7, 2017

2. Cybersecurity and Privacy are two different concepts, however
The Cybersecurity Framework by NIST is widely recognized: adopted by private sector as well
Review of Cybersecurity Framework identified that privacy protection is NOT well defined and therefore not necessarily well protected in federal systems

3. Enter . . .

4. An Engineering Approach to Privacy
(A Systems Approach)

5. Relationship Between Information Security and Privacy: now working on Privacy

6. The Privacy Framework
In January 2017, NIST released An Introduction to Privacy Engineering and Risk Management in Federal Systems
An Engineering Approach to Privacy
Components for Privacy Engineering in Federal Systems
Privacy Engineering Objectives
Predictability
Manageability
Disassociability
Introducing a Privacy Risk Model
Privacy Risk Factors
Privacy Risk Characteristics

7. Privacy Engineering: Objectives

9. Privacy Objectives support the Circular A-130 FIPPs
Access and Amendment
Accountability
Authority
Minimization
Quality and Integrity
Individual Participation
Purpose Specification and Use Limitation
Security
Transparency

10. Aligning A-130 FIPPs with the Privacy and Security Objectives

11. Focus on Predictability

12. What does Predictability really mean
What does Predictability really mean? (Especially in an era of quickly changing technology)
“A reliable sense of what is occurring with PII in a system is core to building trust and accountability”
“By framing predictability in terms of reliable assumptions, agencies can begin to measure more concretely the capabilities in a system that supports these principles”
“If system owners and operators can reliably describe what is occurring with PII, they can better maintain accountability for system compliance with organizational privacy policies and system privacy requirements”
“Predictability is about designing systems so that stakeholders are not surprised by the handling of PII”

13. The Meaning and Application of Predictability: Comparison to Legal Concepts
Patent Law and Nonobviousness
Reasonableness
NOTE: 1) these are analogies and comparisons, not direct applications, and 2) we include analysis of the impact of broader acceptance by the private sector

14. Patent Law: Predictable=Obvious Improvement Predictability is bad for the patent applicant but good for the privacy engineer.
When an inventor improves upon an existing, patent protected technology or product, the improvement itself must be non-obvious in order to obtain a patent. The legal determination of whether the improvement is obvious, and therefore not patentable, invokes the question of whether the improvement upon, or a different use of, an existing invention is predictable.
2011 patent drawing for an improved method of delivering shaving lotion via soft pads on a razor

15. Determining Predictability
Prior Art will be considered to determine nonobviousness
By analogy, determining prior art for use of PII and privacy protections requires a longitudinal understanding of the use of PII and privacy
This is most pressing in today’s environment of fast changing data uses, similar to improvements on patented products
In KSR International Co. v. Teleflex Inc. (KSR), the Supreme Court stated that: “When a work is available in one field of endeavor, design incentives and other market forces can prompt variations of it, either in the same field or a different one. If a person of ordinary skill can implement a predictable variation, § 103 likely bars its patentability.”

16. Two ways of viewing predictability for improvements:
“the improvement is more than the predictable use of prior art elements according to their established functions.” OR
“[t]he combination of familiar elements according to known methods is likely to be obvious when it does no more than yield predictable results.” KSR (2007)
Cotropia: Type I and Type II predictability. Type I is a gap analysis, Type II suffers from hindsight bias
DANGER: Type II predictability induces Hindsight Bias for use of personal data under NIST predictability

17. Mapping Your Home---Sharing the Information with Smart Home/Smart Cities?

18. Reasonableness The “Reasonable Man” The “Ordinary Man”
The “Reasonable Person”
The “Reasonable Woman”
The “Ordinary Man”
The “Average Joe”
The “Man on the Clapham Omnibus”
The “Man on the Street”

19. Katz v. United States (1967)

20. Katz v. United States (1967) The Two-Prong Test
[F]irst that a person have established an actual (subjective) expectation of privacy and
[S]econd, that the expectation be one that society is prepared to recognize as “reasonable”
The “Reasonable Expectation of Privacy” Test

21. Katz v. U.S. The Reality The Katz test should be just one prong
an objective test
That’s what had been proposed
That’s what courts have actually applied

22. The Hope for Predictability