Privacy Engineering Conference

This Call for Proposals (CfP) is open for:

1. Individuals/companies to submit presentation ideas (see Session Format to fine-tune ideas).
2. Suggest topics for someone else to speak/teach/write. (Again, see Session Format to fine-tune ideas.)

Audience for privacy engineering conference and build-up events:

1. Privacy engineers
2. Security professionals/practitioners
3. Crypto researchers and practitioners
4. Software developers
5. Academia, where work on privacy and technology is being carried out
6. Product managers
7. Designers working on integrating privacy in product/interface design.
8. Business owners, including founders and members of CXO teams, who front-face with customers and regulators.
9. Marketing tech professionals who have to comply with regulations that prevent profiling and targeting on the basis of individual data.

If you are one of the above - or someone who have to work with privacy tech (directly/indirectly), you should consider submitting a presentation for speaking (or a topic for someone else to speak).

Session formats:
This conference - and the build-up activities - are accepting proposals for:

1. Workshops - 3 hours, 6 hours or 2 days duration
2. Talks on privacy engineering and design approaches, as used in practice - 20 mins, 40 mins and 60 mins
3. Showcase of in-house solutions, tech stacks and workarounds devised for compliance and privacy - 20 min and 40 min demo sessions
4. Birds of Feather (BOF) sessions - 60-90 mins
5. Round table ideas - with defined target segments
6. Content creation (and collaboration) ideas - checklists, guides, etc.
7. Format of your choice

Topics to consider submitting presentation ideas (and suggesting topics):

1. Privacy protocols and standards. For e.g., data minimisation, differential privacy, privacy by design, privacy by default.
2. End-to-end encryption protocols and engineering. For e.g., Signal Protocol, Matrix Protocol, Disappearing messages, E2E with WebRTC for communications.
3. Privacy audits; analysis of information systems. For e.g., privacy violations, forensics and third-party data sharing.
4. Data anonymisation practices and standards; re-identification attacks. For e.g., anonymizing health data, re-identification of health data, similar issues for MarTech.
5. Privacy Preserving Analytics, Issues of TradeOffs between Utility and Privacy.
6. Alternative data practices such as synthetic data for Machine Learning and AI; techniques to measure and detect machine bias.
7. Computing over-sensitive data using new age techniques. For e.g., homomorphic encryption, Private Information Retrieval (PIR) algorithms.
8. Trust in systems and algorithms with cryptography. For e.g., Applied cryptographic algorithms and practice.
9. Approaches and solutions built for decentralised data structures and architecture design, with focus on privacy.
10. Protocols and frameworks for data collection and sharing. For e.g., Responsible Data Practices, designing data exchanges.
11. Open source engineering solutions for privacy - anything you are working on, building in-house.
12. Ethnographic studies of privacy engineering in technology production. For e.g., implementation and usage of privacy techniques and practices, in the fields of health, governance, education, employment.

Contact details: For queries, write to fifthelephant.editorial@hasgeek.com or call 7676332020.