Towards Secure and Trustworthy Crowdsourcing with Versatile Data Analytics

Crowdsourcing enables the harnessing of crowd wisdom for data collection. While being widely successful, almost all existing crowdsourcing platforms store and process plaintext data only. Such a practice would allow anyone gaining access to the platform (e.g., attackers, administrators) to obtain the sensitive data, raising potential security and privacy concerns. If actively exploited, this not only infringes the data ownership of the crowdsourcing requester who solicits data, but also leaks the privacy of the workers who provide data. In this paper, we envision a crowdsourcing platform with built-in end-to-end encryption (E2EE), where the crowdsourced data remains always-encrypted secret to the platform. Such a design would serve as an in-depth defence strategy against data breach from both internal and external threats, and provide technical means for crowdsourcing service providers to meet various stringent regulatory compliance. We will discuss the technical requirements and related challenges to make this vision a reality, including: 1) assuring high-quality crowdsourced data to enhance data values, 2) enabling versatile data analytics to uncover data insights, 3) protecting data at the front-end to fully achieve E2EE, and 4) preventing the abuse of E2EE for practical deployment. We will briefly overview the limitations of prior arts in meeting all these requirements, and identify a few potential research directions for the roadmap ahead.