This Call for Proposals (CfP) is open for:
- Individuals/companies to submit presentation ideas (see Session Format to fine-tune ideas).
- 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:
- Privacy engineers
- Security professionals/practitioners
- Crypto researchers and practitioners
- Software developers
- Academia, where work on privacy and technology is being carried out
- Product managers
- Designers working on integrating privacy in product/interface design.
- Business owners, including founders and members of CXO teams, who front-face with customers and regulators.
- 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).
This conference - and the build-up activities - are accepting proposals for:
- Workshops - 3 hours, 6 hours or 2 days duration
- Talks on privacy engineering and design approaches, as used in practice - 20 mins, 40 mins and 60 mins
- Showcase of in-house solutions, tech stacks and workarounds devised for compliance and privacy - 20 min and 40 min demo sessions
- Birds of Feather (BOF) sessions - 60-90 mins
- Round table ideas - with defined target segments
- Content creation (and collaboration) ideas - checklists, guides, etc.
- Format of your choice
Topics to consider submitting presentation ideas (and suggesting topics):
- Privacy protocols and standards. For e.g., data minimisation, differential privacy, privacy by design, privacy by default.
- End-to-end encryption protocols and engineering. For e.g., Signal Protocol, Matrix Protocol, Disappearing messages, E2E with WebRTC for communications.
- Privacy audits; analysis of information systems. For e.g., privacy violations, forensics and third-party data sharing.
- Data anonymisation practices and standards; re-identification attacks. For e.g., anonymizing health data, re-identification of health data, similar issues for MarTech.
- Privacy Preserving Analytics, Issues of TradeOffs between Utility and Privacy.
- Alternative data practices such as synthetic data for Machine Learning and AI; techniques to measure and detect machine bias.
- Computing over-sensitive data using new age techniques. For e.g., homomorphic encryption, Private Information Retrieval (PIR) algorithms.
- Trust in systems and algorithms with cryptography. For e.g., Applied cryptographic algorithms and practice.
- Approaches and solutions built for decentralised data structures and architecture design, with focus on privacy.
- Protocols and frameworks for data collection and sharing. For e.g., Responsible Data Practices, designing data exchanges.
- Open source engineering solutions for privacy - anything you are working on, building in-house.
- 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 email@example.com or call 7676332020.
Venkata Pingali (@pingali)
Session format: Talk - 40 mins