相关论文: Privacy-accuracy trade-offs in noisy digital expos…
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…
With the recent surge of social networks like Facebook, new forms of recommendations have become possible - personalized recommendations of ads, content, and even new friend and product connections based on one's social interactions. Since…
Group based anonymization is the most widely studied approach for privacy preserving data publishing. This includes k-anonymity, l-diversity, and t-closeness, to name a few. The goal of this paper is to raise a fundamental issue on the…
Privacy preserving data publishing has attracted considerable research interest in recent years. Among the existing solutions, {\em $\epsilon$-differential privacy} provides one of the strongest privacy guarantees. Existing data publishing…
Throughout the course of the COVID-19 pandemic, several countries have developed and released contact tracing and exposure notification smartphone applications (apps) to help slow the spread of the disease. To support such apps, Apple and…
This research addresses privacy protection in Natural Language Processing (NLP) by introducing a novel algorithm based on differential privacy, aimed at safeguarding user data in common applications such as chatbots, sentiment analysis, and…
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…
Many digital solutions mainly involving Bluetooth technology are being proposed for Contact Tracing Apps (CTA) to reduce the spread of COVID-19. Concerns have been raised regarding privacy, consent, uptake required in a given population,…
As we await a vaccine, social-distancing via efficient contact tracing has emerged as the primary health strategy to dampen the spread of COVID-19. To enable efficient digital contact tracing, we present a novel system to estimate pair-wise…
Mitigation strategies that remove infectious individuals from the greater population have to balance their efficacy with the economic effects associated with quarantine and have to contend with the limited resources available to the public…
The outbreak of COVID-19 pandemic has exposed an urgent need for effective contact tracing solutions through mobile phone applications to prevent the infection from spreading further. However, due to the nature of contact tracing, public…
Differential privacy protects an individual's privacy by perturbing data on an aggregated level (DP) or individual level (LDP). We report four online human-subject experiments investigating the effects of using different approaches to…
Differential privacy is a notion of privacy that has become very popular in the database community. Roughly, the idea is that a randomized query mechanism provides sufficient privacy protection if the ratio between the probabilities that…
In an Internet of Things network, multiple sensors send information to a fusion center for it to infer a public hypothesis of interest. However, the same sensor information may be used by the fusion center to make inferences of a private…
Emerging systems such as smart grids or intelligent transportation systems often require end-user applications to continuously send information to external data aggregators performing monitoring or control tasks. This can result in an…
The inevitable leakage of privacy as a result of unrestrained disclosure of personal information has motivated extensive research on robust privacy-preserving mechanisms. However, existing research is mostly limited to solving the problem…
The proliferation of mobile applications and the subsequent sharing of personal data with service and application providers have given rise to substantial privacy concerns. Application marketplaces have introduced mechanisms to conform to…
In response to calls for open data and growing privacy threats, organizations are increasingly adopting privacy-preserving techniques such as differential privacy (DP) that inject statistical noise when generating published datasets. These…
This document presents an evolution of the ROBERT protocol that decentralizes most of its operations on the mobile devices. DESIRE is based on the same architecture than ROBERT but implements major privacy improvements. In particular, it…
Despite recent widespread deployment of differential privacy, relatively little is known about what users think of differential privacy. In this work, we seek to explore users' privacy expectations related to differential privacy.…