Physical Sciences and Mathematics Commons^™

Sybmatch: Sybil Detection For Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Kan Yang, Yinghui Zhang, Xiaohua Jia, Robert H. Deng

Research Collection School Of Computing and Information Systems

The past decade has witnessed the rise of crowdsourcing, and privacy in crowdsourcing has also gained rising concern in the meantime. In this paper, we focus on the privacy leaks and sybil attacks during the task matching, and propose a privacy-preserving task matching scheme, called SybMatch. The SybMatch scheme can simultaneously protect the privacy of publishers and subscribers against semi-honest crowdsourcing service provider, and meanwhile support the sybil detection against greedy subscribers and efficient user revocation. Detailed security analysis and thorough performance evaluation show that the SybMatch scheme is secure and efficient.

Anonymous Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Xiaohua Jia, Kan Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the development of sharing economy, crowdsourcing as a distributed computing paradigm has become increasingly pervasive. As one of indispensable services for most crowdsourcing applications, task matching has also been extensively explored. However, privacy issues are usually ignored during the task matching and few existing privacy-preserving crowdsourcing mechanisms can simultaneously protect both task privacy and worker privacy. This paper systematically analyzes the privacy leaks and potential threats in the task matching and proposes a single-keyword task matching scheme for the multirequester/multiworker crowdsourcing with efficient worker revocation. The proposed scheme not only protects data confidentiality and identity anonymity against the crowd-server, …

A Data-Driven Analysis Of Workers' Earnings On Amazon Mechanical Turk, Kotaro Hara, Abigail Adams, Kristy Milland, Saiph Savage, Chris Callison-Burch, Jeffrey P. Bigham

Research Collection School Of Computing and Information Systems

A growing number of people are working as part of on-line crowd work. Crowd work is often thought to be low wage work. However, we know little about the wage distribution in practice and what causes low/high earnings in this setting. We recorded 2,676 workers performing 3.8 million tasks on Amazon Mechanical Turk. Our task-level analysis revealed that workers earned a median hourly wage of only ~$2/h, and only 4% earned more than $7.25/h. While the average requester pays more than $11/h, lower-paying requesters post much more work. Our wage calculations are influenced by how unpaid work is accounted for, …

The Hydrocolor App: Above Water Measurements Of Remote Sensing Reflectance And Turbidity Using A Smartphone Camera, Thomas Leeuw, Emmanuel S. Boss

Marine Sciences Faculty Scholarship

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. HydroColor is a mobile application that utilizes a smartphone’s camera and auxiliary sensors to measure the remote sensing reflectance of natural water bodies. HydroColor uses the smartphone’s digital camera as a three-band radiometer. Users are directed by the application to collect a series of three images. These images are used to calculate the remote sensing reflectance in the red, green, and blue broad wavelength bands. As with satellite measurements, the reflectance can be inverted to estimate the concentration of absorbing and scattering substances in the water, which are predominately composed of …

Smart Cities And Urban Management, Singapore Management University

Research Collection Office of Research

In this booklet, read about SMU’s research and initiatives related to smart cities and urban management, and how we strive to make meaningful impact on business, government and society for Singapore and beyond.

Contents:

Liveability and quality of life

• Community participation through mobile crowdsourcing
• Smarter, healthier eating with Food AI
• Data-driven community eldercare platform for sustainable ageing-in-place
• A date with AI
• Smart mobility accessibility for barrier-free access
• Food security

Optimisation and resource management

• Collaborative urban delivery optimisation
• Seat occupancy detection through capacitance sensing
• Large-scale crowd simulation based on real-world data
• Gaining insights through Wi-Fi technology
• Taxi driver guidance system
• Efficiency …

Smartphone User Privacy Preserving Through Crowdsourcing, Bahman Rashidi

Theses and Dissertations

In current Android architecture, users have to decide whether an app is safe to use or not. Expert users can make savvy decisions to avoid unnecessary private data breach. However, the majority of regular users are not technically capable or do not care to consider privacy implications to make safe decisions. To assist the technically incapable crowd, we propose a permission control framework based on crowdsourcing. At its core, our framework runs new apps under probation mode without granting their permission requests up-front. It provides recommendations on whether to accept or not the permission requests based on decisions from peer …

Slade: A Smart Large-Scale Task Decomposer In Crowdsourcing, Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou

Research Collection School Of Computing and Information Systems

Crowdsourcing has been shown to be effective in a wide range of applications, and is seeing increasing use. A large-scale crowdsourcing task often consists of thousands or millions of atomic tasks, each of which is usually a simple task such as binary choice or simple voting. To distribute a large-scale crowdsourcing task to limited crowd workers, a common practice is to pack a set of atomic tasks into a task bin and send to a crowd worker in a batch. It is challenging to decompose a large-scale crowdsourcing task and execute batches of atomic tasks, which ensures reliable answers at …