In many mobile crowdsensing scenarios it is desirable to give micro-payments to contributors as an incentive for their participation. However, to further encourage participants to use the system, one important requirement is protection of user privacy. In this work we present a reverse auction mechanism as an efficient way to offer incentives to users by allowing them to determine their own pri...

Participatory or crowd-sensing applications process sensory data contributed by users and transform them to simple visualizations (such as for example noise or pollution levels) that help create an accurate representation of the surrounding environment. Although contributed data is of great interest to individuals, the involvement of citizens and community groups, however, is still limited. Hen...

We propose a modeling of the problem of privacy-compliant data publishing that captures confidentiality constraints on one side and visibility requirements on the other side. Confidentiality constraints express the fact that some attributes, or associations among them, are sensitive and cannot be released. Visibility requirements express requests for views over data that should be provided. We ...

The number of video surveillance deployments in publicly accessible spaces is continuously increasing. At the same time, the call for technical assistance of human operators in terms of so-called smart video surveillance system has been growing ever louder and is addressed by research and development. With such systems, video analysis algorithms for activity recognition, tracking, and biometric...

When in physical proximity, data can be directly exchanged between the mobile devices people carry — for example over Bluetooth. If people cooperate to store, carry and forward messages on one another’s behalf, then an opportunistic network may be formed, independent of any fixed infrastructure. To enable performant routing within opportunistic networks, use of social network information has be...

Electronic Identity (eID) cards are rapidly emerging in Europe and are gaining user acceptance. As an authentication token, an eID card is a gateway to personal information and as such it is subject to privacy risks. Several European countries have taken extra care to protect their citizens against these risks. A notable example is the German eID card, which we take as a case study in this pape...

Abstract In this paper we present LiM (‘Less is More’), a malware classification framework that leverages Federated Learning to detect and classify malicious apps in privacy-respecting manner. Information about newly installed kept locally on users’ devices, so the provider cannot infer which were by users. At same time, input from all users taken into account federated learning process they be...

Web personalization has demonstrated to be advantageous for both online customers and vendors. However, its benefits may be severely counteracted by privacy constraints. Personalized systems need to take users’ privacy concerns into account, as well as privacy laws and industry self-regulation that may be in effect. In this paper, we first discuss how these constraints may affect web-based pers...

A major challenge for machine learning is increasing the availability of data while respecting the privacy of individuals. Differential privacy is a framework which allows algorithms to have provable privacy guarantees. Gaussian processes are a widely used approach for dealing with uncertainty in functions. This paper explores differentially private mechanisms for Gaussian processes. We compare...

Traditional utility metering is to be replaced by smart metering. Smart metering enables very fine grained utility consumption measurements. These fine grained measurements raise privacy concerns due to the lifestyle information which can be inferred from the precise time at which utilities were consumed. This paper outlines two privacy respecting time of use billing protocols for smart meterin...