Location Privacy in Spatial Crowdsourcing

نویسندگان

  • Hien To
  • Cyrus Shahabi
چکیده

Spatial crowdsourcing (SC) is a new platform that engages individuals in collecting and analyzing environmental, social and other spatiotemporal information. With SC, requesters outsource their spatiotemporal tasks (tasks associated with location and time) to a set of workers, who will perform the tasks by physically traveling to the tasks’ locations. However, current solutions require the workers, who in many cases are simply volunteering for a cause, to disclose their locations to untrustworthy entities. Revealing an individual’s location data to other entities may prevent people from contributing to SC applications, thus rendering location privacy a critical obstacle to the growth of SC applications. This chapter first identifies privacy threats toward both workers and requesters during the two main phases of spatial crowdsourcing, tasking and reporting. Tasking is the process of identifying which tasks should be assigned to which workers. This process is handled by a spatial crowdsourcing server (SC-server). The latter phase is reporting, in which workers travel to the tasks’ locations, complete the tasks and upload their reports to the SC-server. The challenge is to enable effective and efficient tasking as well as reporting in SC without disclosing the actual locations of workers (at least until they agree to perform a task) and the tasks themselves (at least to workers who are not assigned to those tasks). This chapter aims to provide an overview of the state-of-the-art in protecting users’ location privacy in spatial crowdsourcing. We provide a comparative study of a diverse set of solutions in terms of task publishing modes (push vs. pull), problem focuses (tasking and reporting), threats (server, requester and worker), and underlying technical approaches (from pseudonymity, cloaking, and perturbation to exchangebased and encryption-based techniques). The strengths and drawbacks of the techniques are highlighted, leading to a discussion of open problems and future work. Hien To University of Southern California, Los Angeles, CA 90089 e-mail: [email protected] Cyrus Shahabi University of Southern California, Los Angeles, CA 90089 e-mail: [email protected]

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Understanding the Valuation of Location Privacy: a Crowdsourcing-Based Approach

The exchange of private information for services or other benefits is a commonplace practice today in the advent of mobile technology. In the case of mobile services, the exchanged commodity is increasingly often spatial location of the user. To decide whether this transaction is beneficial, the user needs to evaluate the exchange value of this commodity. To assess the value users give to their...

متن کامل

Protecting Location Privacy in Spatial Crowdsourcing using Encrypted Data

In spatial crowdsourcing, spatial tasks are outsourced to a set of workers in proximity of the task locations for efficient assignment. It usually requires workers to disclose their locations, which inevitably raises security concerns about the privacy of the workers’ locations. In this paper, we propose a secure SC framework based on encryption, which ensures that workers’ location information...

متن کامل

Spatial Crowdsourcing: Challenges, Techniques, and Applications

Crowdsourcing is a new computing paradigm where humans are actively enrolled to participate in the procedure of computing, especially for tasks that are intrinsically easier for humans than for computers. The popularity of mobile computing and sharing economy has extended conventional webbased crowdsourcing to spatial crowdsourcing (SC), where spatial data such as location, mobility and the ass...

متن کامل

Privacy-Preserving Online Task Assignment in Spatial Crowdsourcing with Untrusted Server

With spatial crowdsourcing (SC), requesters outsource their spatiotemporal tasks (tasks associated with location and time) to a set of workers, who will perform the tasks by physically traveling to the tasks’ locations. However, current solutions require the locations of the workers and/or the tasks to be disclosed to untrusted parties (SC server) for effective assignments of tasks to workers. ...

متن کامل

Security and Privacy Issues

C rowdsensing—the crowdsourcing of sensor data—allows for real-time data gathering with greater reach and accessibility than traditional crowdsourcing, because it leverages personal mobile devices as its sensor nodes (see Figure 1). This makes large-scale participatory sensing viable with little or no infrastructure cost, and because mobile device users can freely move around, coverage of senso...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1704.06860  شماره 

صفحات  -

تاریخ انتشار 2017