ICSI

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Visible to the public Scalable Privacy Analysis

One major shortcoming of the current "notice and consent" privacy framework is that the constraints for data usage stated in policies--be they stated privacy practices, regulation, or laws--cannot easily be compared against the technologies that they govern. To that end, we are developing a framework to automatically compare policy against practice. Broadly, this involves identifying the relevant data usage policies and practices in a given domain, then measuring the real-world exchanges of data restricted by those rules.

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Visible to the public Contextual Integrity for Computer Systems

Despite the success of Contextual Integrity (see project "Operationalizing Contextual Integrity"), its uptake by computer scientists has been limited due to the philosophical framework not meeting them on their terms. In this project we will both refine Contextual Integrity (CI) to better fit the problems computer scientists face and to express it in the mathematical terms they expect.

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Visible to the public Operationalizing Contextual Integrity

According to Nissenbaum's theory of contextual integrity (CI), protecting privacy means ensuring that personal information flows appropriately; it does not mean that no information flows (e.g., confidentiality), or that it flows only if the information subject allows it (e.g., control). Flow is appropriate if it conforms to legitimate, contextual informational norms. Contextual informational norms prescribe information flows in terms of five parameters: actors (sender, subject, recipient), information types, and transmission principles.

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Visible to the public Governance for Big Data

Privacy governance for Big Data is challenging--data may be rich enough to allow the inference of private information that has been removed, redacted, or minimized. We must protect against both malicious and accidental inference, both by data analysts and by automated systems. To do this, we are extending existing methods for controlling the inference risks of common analysis tools (drawn from literature on the related problem of nondiscriminatory data analysis). We are coupling these methods with auditing tools such as verifiably integral audit logs.

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Visible to the public Designing for Privacy

Methods, approaches, and tools to identify the correct conceptualization of privacy early in the design and engineering process are important. For example, early whole body imaging technology for airport security were analyzed by the Department of Homeland Security through a Privacy Impact Assessment, focusing on the collection of personally identifiable information finding that the images of persons' individual bodies were not detailed enough to constitute PII, and would not pose a privacy problem.