An efficient task matching schema with signature oriented encryption technique

Abstract

Crowdsourcing platforms have transformed task outsourcing by enabling large-
scale human collaboration over the internet. A key factor in their success is the
efficient matching of workers to tasks based on individual skills and preferences.
However, this process often involves sharing sensitive personal data, raising seri-
ous concerns about privacy and security. Existing solutions, such as traditional
encryption and proxy re-encryption, struggle to balance scalability with strong
privacy guarantees. In this paper, we propose a privacy-preserving task-matching
framework that utilizes ring verification signatures to safeguard user anonymity
and ensure data integrity. Unlike conventional methods, our approach removes
the dependency on proxy re-encryption and effectively mitigates risks related to
identity inference. We detail the system’s design, implementation, and security
analysis, demonstrating its practical effectiveness in preserving privacy within
dynamic and large-scale crowdsourcing environments.