Related papers: The tradeoff between the utility and risk of locat…
Today's age of data holds high potential to enhance the way we pursue and monitor progress in the fields of development and humanitarian action. We study the relation between data utility and privacy risk in large-scale behavioral data,…
Due to the recent popularity of online social networks, coupled with people's propensity to disclose personal information in an effort to achieve certain gratifications, the problem of navigating the tradeoff between privacy and utility…
Firms collect vast amounts of behavioral and geographical data on individuals. While behavioral data captures an individual's digital footprint, geographical data reflects their physical footprint. Given the significant privacy risks…
While the entire field of privacy preserving data analytics is focused on the privacy-utility tradeoff, recent work has shown that privacy preserving data publishing can introduce different levels of utility across different population…
As the reliance on GPS technology for navigation grows, so does the ethical dilemma of balancing its indispensable utility with the escalating concerns over user privacy. This study investigates the trade-offs between GPS utility and…
The modernization of the electrical grid and the installation of smart meters come with many advantages to control and monitoring. However, in the wrong hands, the data might pose a privacy threat. In this paper, we consider the tradeoff…
Ensuring the usefulness of electronic data sources while providing necessary privacy guarantees is an important unsolved problem. This problem drives the need for an analytical framework that can quantify the safety of personally…
With the ubiquitous use of location-based services, large-scale individual-level location data has been widely collected through location-awareness devices. The widespread exposure of such location data poses significant privacy risks to…
Privacy-preserving data release mechanisms aim to simultaneously minimize information-leakage with respect to sensitive data and distortion with respect to useful data. Dependencies between sensitive and useful data results in a…
When sensitive information is encoded in data, it is important to ensure the privacy of information when attempting to learn useful information from the data. There is a natural tradeoff whereby increasing privacy requirements may decrease…
Advances in sensing and communication capabilities as well as power industry deregulation are driving the need for distributed state estimation in the smart grid at the level of the regional transmission organizations (RTOs). This leads to…
The pervasiveness of Internet of Things results in vast volumes of personal data generated by smart devices of users (data producers) such as smart phones, wearables and other embedded sensors. It is a common requirement, especially for Big…
Every time the customer (individual or company) has to release personal information to its service provider (e.g., an online store or a cloud computing provider), it faces a trade-off between the benefits gained (enhanced or cheaper…
Machine learning is increasingly used in the most diverse applications and domains, whether in healthcare, to predict pathologies, or in the financial sector to detect fraud. One of the linchpins for efficiency and accuracy in machine…
As smart meters continue to be deployed around the world collecting unprecedented levels of fine-grained data about consumers, we need to find mechanisms that are fair to both, (1) the electric utility who needs the data to improve their…
Mobile crowdsensing has emerged as an efficient sensing paradigm which combines the crowd intelligence and the sensing power of mobile devices, e.g.,~mobile phones and Internet of Things (IoT) gadgets. This article addresses the…
Location and mobility patterns of individuals are important to environmental planning, societal resilience, public health, and a host of commercial applications. Mining telecommunication traffic and transactions data for such purposes is…
Cellular providers and data aggregating companies crowdsource celluar signal strength measurements from user devices to generate signal maps, which can be used to improve network performance. Recognizing that this data collection may be at…
We propose a novel problem formulation to address the privacy-utility tradeoff, specifically when dealing with two distinct user groups characterized by unique sets of private and utility attributes. Unlike previous studies that primarily…
A geo-marketplace allows users to be paid for their location data. Users concerned about privacy may want to charge more for data that pinpoints their location accurately, but may charge less for data that is more vague. A buyer would…