相关论文: Spatial K-anonymity: A Privacy-preserving Method f…

Although the bulk of the research in privacy and statistical disclosure control is designed for cross-sectional data, i.e. data where individuals are observed at one single point in time, longitudinal data, i.e. individuals observed over…

Human mobility data is a crucial resource for urban mobility management, but it does not come without personal reference. The implementation of security measures such as anonymization is thus needed to protect individuals' privacy. Often, a…

Cooperative spectrum sensing, despite its effectiveness in enabling dynamic spectrum access, suffers from location privacy threats, merely because secondary users (SUs)' sensing reports that need to be shared with a fusion center to make…

Publishing datasets plays an essential role in open data research and promoting transparency of government agencies. However, such data publication might reveal users' private information. One of the most sensitive sources of data is…

We consider the problem of privacy in direct communications, showing how quantum mechanics can be useful to guarantee a certain level of confidentiality. In particular, we review a continuous variable approach recently proposed by us [S.…

In this demonstration, we present a privacy-preserving epidemic surveillance system. Recently, many countries that suffer from coronavirus crises attempt to access citizen's location data to eliminate the outbreak. However, it raises…

For the protection of people and society against harm and health threats -- especially for the COVID-19 pandemic -- a variety of different disciplines needs to be involved. The data collection of very basic and health-related data of…

Camouflaging data by generating fake information is a well-known obfuscation technique for protecting data privacy. In this paper, we focus on a very sensitive and increasingly exposed type of data: location data. There are two main…

Homomorphic encryption, secure multi-party computation, and differential privacy are part of an emerging class of Privacy Enhancing Technologies which share a common promise: to preserve privacy whilst also obtaining the benefits of…

The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively…

Sharing sensitive data is vital in enabling many modern data analysis and machine learning tasks. However, current methods for data release are insufficiently accurate or granular to provide meaningful utility, and they carry a high risk of…

The pandemic in 2020 and 2021 had enormous economic and societal consequences, and studies show that contact tracing algorithms can be key in the early containment of the virus. While large strides have been made towards more effective…

To fight against infectious diseases (e.g., SARS, COVID-19, Ebola, etc.), government agencies, technology companies and health institutes have launched various contact tracing approaches to identify and notify the people exposed to…

Due to the pervasiveness of image capturing devices in every-day life, images of individuals are routinely captured. Although this has enabled many benefits, it also infringes on personal privacy. A promising direction in research on…

The 2019 Coronavirus disease (COVID-19) pandemic, caused by a quick dissemination of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has had a deep impact worldwide, both in terms of the loss of human life and the economic…

Differential Privacy (DP) has emerged as a pivotal approach for safeguarding individual privacy in data analysis, yet its practical adoption is often hindered by challenges in the implementation and communication of DP. This paper presents…

The COVID19 pandemic spread across the world in late 2019 and early 2020. As the pandemic spread, technologists joined forces with public health officials to develop apps to support COVID19 response. Yet, for these technological solutions…

In their efforts to tackle the COVID-19 crisis, decision makers are considering the development and use of smartphone applications for contact tracing. Even though these applications differ in technology and methods, there is an increasing…

Vision-Language Models (VLMs) such as GPT-4o now demonstrate a remarkable ability to infer users' locations from public shared images, posing a substantial risk to geoprivacy. Although adversarial perturbations offer a potential defense,…

As multiple adverse events in 2021 illustrated, virtually all aspects of our societal functioning -- from water and food security to energy supply to healthcare -- more than ever depend on the dynamics of environmental factors.…