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众包中的隐私保护任务匹配和多次提交检测。

Privacy-Preserving Task-Matching and Multiple-Submissions Detection in Crowdsourcing.

机构信息

The School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing 100876, China.

The National Engineering Laboratory for Mobile Network Security, Beijing 100876, China.

出版信息

Sensors (Basel). 2021 Apr 26;21(9):3036. doi: 10.3390/s21093036.

DOI:10.3390/s21093036
PMID:33925947
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8123452/
Abstract

Crowdsourcing enables requesters to publish tasks to a platform and workers are rewarded for performing tasks of interest. It provides an efficient and low-cost way to aggregate data and solve problems that are difficult for computers but simple for humans. However, the privacy risks and challenges are still widespread. In the real world, the task content may be sensitive and only workers who meet specific requirements or possess certain skills are allowed to acquire and perform it. When these distributed workers submit their task answers, their identity or attribute privacy may also be exposed. If workers are allowed to submit anonymously, they may have the chance to repeat their answers so as to get more rewards. To address these issues, we develop a privacy-preserving task-matching and multiple-submissions detection scheme based on inner-product cryptography and proof of knowledge (PoK) protocol in crowdsourcing. In such a construction, multi-authority inner-product encryption is introduced to protect task confidentiality and achieve fine-grained task-matching based on the attributes of workers. The PoK protocol helps to restrict multiple submissions. For one task, a suitable worker could only submit once without revealing his/her identity. Moreover, different tasks for one worker are unlinkable. Furthermore, the implementation analysis shows that the scheme is effective and feasible.

摘要

众包使请求者能够将任务发布到平台上,而工人则因执行感兴趣的任务而获得奖励。它提供了一种高效、低成本的方式来聚合数据和解决对计算机来说困难但对人类来说简单的问题。然而,隐私风险和挑战仍然很普遍。在现实世界中,任务内容可能是敏感的,只有符合特定要求或具备特定技能的工人才能获得和执行任务。当这些分布式工人提交他们的任务答案时,他们的身份或属性隐私也可能会被暴露。如果允许工人匿名提交,他们可能有机会重复提交答案以获得更多奖励。为了解决这些问题,我们在众包中开发了一种基于内积密码学和知识证明(PoK)协议的隐私保护任务匹配和多次提交检测方案。在这种结构中,引入了多授权者内积加密来保护任务机密性,并基于工人的属性实现细粒度的任务匹配。PoK 协议有助于限制多次提交。对于一个任务,合适的工人只能提交一次,而不泄露其身份。此外,一个工人的不同任务是不可链接的。此外,实现分析表明该方案是有效和可行的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/06e3ad1b5c47/sensors-21-03036-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/2587edd9397c/sensors-21-03036-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/bbf7395d70fc/sensors-21-03036-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/81bda2b4a15b/sensors-21-03036-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/c2840bbdcfd1/sensors-21-03036-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/06e3ad1b5c47/sensors-21-03036-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/2587edd9397c/sensors-21-03036-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/bbf7395d70fc/sensors-21-03036-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/81bda2b4a15b/sensors-21-03036-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/c2840bbdcfd1/sensors-21-03036-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78b8/8123452/06e3ad1b5c47/sensors-21-03036-g005.jpg

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