Directions in Privacy Assistance Technologies

Keynote by Nina Taft

Wednesday, 1 March 2023
9:00am – 10:00am

Smartphone app developers face numerous challenges in improving their privacy posture that stem from continually evolving laws, policies, user opinions, and the need for specific expertise. Users face challenges in managing their privacy due to ambiguous and evolving privacy controls, as well as inconsistent experiences across apps and services.

In this talk we focus on opportunities to provide privacy assistance to both developers and users. We’ll briefly summarize user privacy assistance methods, showing a few examples of success and discussing some challenges therein. We primarily focus on privacy assistance for developers. Considerable progress has been achieved in using Natural Language Processing techniques to automatically analyze privacy policies, and this has encouraged the development of tools that give developers critical advice. Advances in Natural Language Understanding and Large Language Models also provide opportunities to understand user opinions by analyzing text corpuses such as app reviews; thereby providing the opportunity to study user privacy perspectives from millions of users. 

We will discuss how these techniques provide opportunities to accelerate a developer’s ability to be responsive to user issues impacting trust, and the evolving legal and regulatory landscape.

Nina Taft photograph

Keynote Speaker: Nina Taft

Nina Taft is a Senior Staff Research Scientist at Google where she leads the Applied Privacy Research group. Nina received her PhD from UC Berkeley, and has worked in industrial research labs since then – at SRI, Sprint Labs, Intel Berkeley Labs, and Technicolor Research – before joining Google. 

For many years, Nina worked in the field of networking, focused on Internet traffic modeling, traffic matrix estimation, network protocols, and intrusion detection. In 2017 she received the top-10 women in networking N2Women award.  In the last decade, she has been working in privacy with a focus on applications of machine learning for privacy, and privacy assistance solutions for both users and developers.

She has been chair of the SIGCOMM, IMC and PAM conferences, has published over 90 papers, holds over 10 patents, and currently serves on the Scientific Advisory Board of the Max Planck Institute.

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