Mon, 9 May, 15:00 - 15:45 UTC
The emerging public awareness and government regulations of data privacy motivate new paradigms of collecting and analyzing data transparent and acceptable to the general public. This demo will show an entirely novel way of collecting and analyzing data, based on a recently proposed notion of data privacy named "Interval Privacy" (to appear in IEEE Transactions on Signal Processing).
In particular, the demo will provide an online link to the ICASSP audience. Each participant will be able to access a randomly generated survey form that asks privacy-sensitive questions (e.g., salary) in the form of "Is your salary higher than X"? Here, the values of X are randomly generated by our backend server (according to our specified mechanisms). Then, a participant may choose to answer or not answer a question. After a few participants (which we expect to be at least ten) have submitted their data, our backend server will immediately show an estimated population average on the webpage. The novelty of the demo is two-fold: 1. This demo shows how a data collector (e.g., a company or government agency) can process signals from incomplete/broken information at an individual level but still obtain accurate population-level information. 2. This demo shows a novel form of survey that, unlike classical surveys with fixed questions/choices, uses randomly generated questions to improve accuracy significantly. 3. Compared with the current data privacy implementations that rely on the data collector to add noise to collected data, this demo shows an entirely novel human-computer interface to guarantee privacy, which is perceptible, transparent, and simple to individuals who own the private data.
The demo is expected to significantly impact signal processing communities by showing a novel way of sharing/collecting sensitive signals interactively and on-the-fly, featuring human-centric signal processing that matches the ICASSP 2022 theme.