Related papers: Privacy-Preserving Payment Splitting
Rapidly changing social norms and national, legal, and political conditions socially constrain people from discussing sensitive topics such as sexuality or religion. Such constrained, vulnerable minorities are often worried about…
Crypto-assets and central bank digital currencies (CBDCs) are reshaping how value is exchanged in distributed computing environments. These systems combine cryptographic primitives, protocol design, and system architectures to provide…
Fair exchange protocols let two mutually distrustful parties exchange digital data in a way that neither party can cheat. They have various applications such as the exchange of digital items, or the exchange of digital coins and digital…
The General Data Protection Regulation (GDPR) aims to ensure that all personal data processing activities are fair and transparent for the European Union (EU) citizens, regardless of whether these are carried out within the EU or anywhere…
The popularity and applicability of mobile crowdsensing applications are continuously increasing due to the widespread of mobile devices and their sensing and processing capabilities. However, we need to offer appropriate incentives to the…
As privacy features in Android operating system improve, privacy-invasive apps may gradually shift their focus to non-standard and covert channels for leaking private user/device information. Such leaks also remain largely undetected by…
Split learning (SL) is a new collaborative learning technique that allows participants, e.g. a client and a server, to train machine learning models without the client sharing raw data. In this setting, the client initially applies its part…
Today, vast amounts of location data are collected by various service providers. These location data owners have a good idea of where their users are most of the time. Other businesses also want to use this information for location…
In anonymous broadcast, one or more parties want to anonymously send messages to all parties. This problem is increasingly important as a black-box in many privacy-preserving applications such as anonymous communication, distributed…
Contact tracing is an effective tool in controlling the spread of infectious diseases such as COVID-19. It involves digital monitoring and recording of physical proximity between people over time with a central and trusted authority, so…
The amount of personal data collected in our everyday interactions with connected devices offers great opportunities for innovative services fueled by machine learning, as well as raises serious concerns for the privacy of individuals. In…
Distributed deep learning frameworks such as split learning provide great benefits with regards to the computational cost of training deep neural networks and the privacy-aware utilization of the collective data of a group of data-holders.…
Smart grids feature a bidirectional flow of electricity and data, enhancing flexibility, efficiency, and reliability in increasingly volatile energy grids. However, data from smart meters can reveal sensitive private information.…
Threshold cryptography has gained momentum in the last decades as a mechanism to protect long term secret keys. Rather than having a single secret key, this allows to distribute the ability to perform a cryptographic operation such as…
Lack of trust between organisations and privacy concerns about their data are impediments to an otherwise potentially symbiotic joint data analysis. We propose DataRing, a data sharing system that allows mutually mistrusting participants to…
Blockchains provide environments where parties can interact transparently and securely peer-to-peer without needing a trusted third party. Parties can trust the integrity and correctness of transactions and the verifiable execution of…
Private blockchain networks are used by enterprises to manage decentralized processes without trusted mediators and without exposing their assets publicly on an open network like Ethereum. Yet external parties that cannot join such networks…
In the digital era, users share their personal data with service providers to obtain some utility, e.g., access to high-quality services. Yet, the induced information flows raise privacy and integrity concerns. Consequently, cautious users…
Crowd sensing is a new paradigm which leverages the pervasive smartphones to efficiently collect sensing data, enabling numerous novel applications. To achieve good service quality for a crowd sensing application, incentive mechanisms are…
Cloud computing enables users to process and store data remotely on high-performance computers and servers by sharing data over the Internet. However, transferring data to clouds causes unavoidable privacy concerns. Here, we present a…