Related papers: Where Trust Fails: Mapping Location-Data Provenanc…
Digital societies increasingly rely on trustworthy proofs of physical presence for services such as supply-chain tracking, e-voting, ride-sharing, and location-based rewards. Yet, traditional localization methods often lack cryptographic…
Reliable use of real-world data requires confidence that recorded evidence reflects what actually occurred at the moment of capture. In adversarial or incentive-misaligned cyber-physical settings, device-centric provenance and post-capture…
With the advent of mobile computing, location-based services have recently gained popularity. Many applications use the location provenance of users, i.e., the chronological history of the users' location for purposes ranging from access…
In an organization specifically as virtual as cloud there is need for access control systems to constrain users direct or backhanded action that could lead to breach of security. In cloud, apart from owner access to confidential data the…
The Internet of Things (IoT) relies on resource-constrained devices deployed in unprotected environments. Given their constrained nature, IoT systems are vulnerable to security attacks. Data provenance, which tracks the origin and flow of…
Proof-of-Location (PoL) is a lightweight security concept for Internet-of-Things (IoT) networks, focusing on the sensor nodes as the least performant and most vulnerable parts of IoT networks. PoL builds on the identification of network…
This paper addresses critical questions surrounding the security of government-issued identity documents and their potential misuse, with an emphasis on understanding the perspectives of ordinary citizens across Europe and the United States…
The interconnection of resource-constrained and globally accessible things with untrusted and unreliable Internet make them vulnerable to attacks including data forging, false data injection, and packet drop that affects applications with…
In recent years, industry leaders and researchers have proposed to use technical provenance standards to address visual misinformation spread through digitally altered media. By adding immutable and secure provenance information such as…
Ensuring the trustworthiness and long-term verifiability of scientific data is a foundational challenge in the era of data-intensive, collaborative research. Provenance metadata plays a key role in this context, capturing the origin,…
Robot behavior is often validated through simulation-based testing, yet the replicability of such campaigns depends critically on transparent documentation of how tests are configured, executed, and post-processed. We argue that data…
New capabilities in foundation models are owed in large part to massive, widely-sourced, and under-documented training data collections. Existing practices in data collection have led to challenges in tracing authenticity, verifying…
Demand is growing for more accountability regarding the technological systems that increasingly occupy our world. However, the complexity of many of these systems - often systems-of-systems - poses accountability challenges. A key reason…
Data provenance collects comprehensive information about the events and operations in a computer system at both application and system levels. It provides a detailed and accurate history of transactions that help delineate the data flow…
Provenance, which traces data from its creation to manipulation, is crucial for ensuring data integrity, reliability, and trustworthiness. It is valuable for single-user applications, collaboration within organizations, and across…
Cloud computing represents a significant economic opportunity for Europe. However, this growth is threatened by adoption barriers largely related to trust. This position paper examines trust and confidence issues in cloud computing and…
Many online services rely on self-reported locations of user devices like smartphones. To mitigate harm from falsified self-reported locations, the literature has proposed location proof services (LPSs), which provide proof of a device's…
Mobility patterns of vehicles and people provide powerful data sources for location-based services such as fleet optimization and traffic flow analysis. Location-based service providers must balance the value they extract from trajectory…
Provenance systems are used to capture history metadata, applications include ownership attribution and determining the quality of a particular data set. Provenance systems are also used for debugging, process improvement, understanding…
Concerns about data privacy are omnipresent, given the increasing usage of digital applications and their underlying business model that includes selling user data. Location data is particularly sensitive since they allow us to infer…