Related papers: Hang With Your Buddies to Resist Intersection Atta…
Research on data confidentiality, integrity and availability is gaining momentum in the ICT community, due to the intrinsically insecure nature of the Internet. While many distributed systems and services are now based on secure…
Operators of online social networks are increasingly sharing potentially sensitive information about users and their relationships with advertisers, application developers, and data-mining researchers. Privacy is typically protected by…
Delegating authentication to identity providers like Google or Facebook, while convenient, compromises user privacy. These identity providers can record users' every move; the global identifiers they provide also enable internet-wide…
Camera-equipped mobile devices, such as phones, smart glasses, and AR headsets, pose a privacy challenge for bystanders, who currently lack effective real-time mechanisms to control the capture of their picture, video, including their face.…
This paper presents Riposte, a new system for anonymous broadcast messaging. Riposte is the first such system, to our knowledge, that simultaneously protects against traffic-analysis attacks, prevents anonymous denial-of-service by…
The task of infectious disease contact tracing is crucial yet challenging, especially when meeting strict privacy requirements. Previous attempts in this area have had limitations in terms of applicable scenarios and efficiency. Our paper…
Distributed Denial-of-Service (DDoS) attacks are usually launched through the $botnet$, an "army" of compromised nodes hidden in the network. Inferential tools for DDoS mitigation should accordingly enable an early and reliable…
We introduce a new class of lower overhead tunnel that is resistant to traffic analysis. The tunnel opportunistically reduces the number of dummy packets transmitted during busy times when many flows are simultaneously active while…
Standardization and harmonization efforts have reached a consensus towards using a special-purpose Vehicular Public-Key Infrastructure (VPKI) in upcoming Vehicular Communication (VC) systems. However, there are still several technical…
The success of applications for sharing GPS trajectories raises serious privacy concerns, in particular about users' home addresses. In this paper we show that a Bayesian approach is natural and effective for a rigorous analysis of…
Federated Learning allows collaborative training without data sharing in settings where participants do not trust the central server and one another. Privacy can be further improved by ensuring that communication between the participants…
Online users generate tremendous amounts of data. To better serve users, it is required to share the user-related data among researchers, advertisers and application developers. Publishing such data would raise more concerns on user…
As autonomous systems begin to operate amongst humans, methods for safe interaction must be investigated. We consider an example of a small autonomous vehicle in a pedestrian zone that must safely maneuver around people in a free-form…
The exchange of personal information in digital environments poses significant risks, including identity theft, privacy breaches, and data misuse. Addressing these challenges requires a deep understanding of user behavior and mental models…
A major limitation of open P2P networks is the lack of strong identities. This allows any agent to attack the system by creating multiple false personas, thereby disrupting the overlay network's connectivity and sabotaging its operation. In…
Anonymity systems such as Tor aim to enable users to communicate in a manner that is untraceable by adversaries that control a small number of machines. To provide efficient service to users, these anonymity systems make full use of…
Mobile ad hoc networks (MANETs) are self-configuring infrastructure-less networks comprised of mobile nodes that communicate over wireless links without any central control on a peer-to-peer basis. These individual nodes act as routers to…
The Internet of Things (IoT) promises to improve user utility by tuning applications to user behavior, but revealing the characteristics of a user's behavior presents a significant privacy risk. Our previous work has established the…
Anonymized data is highly valuable to both businesses and researchers. A large body of research has however shown the strong limits of the de-identification release-and-forget model, where data is anonymized and shared. This has led to the…
Malicious agents pose significant threats to the reliability and decision-making capabilities of Multi-Agent Systems (MAS) powered by Large Language Models (LLMs). Existing defenses often fall short due to reactive designs or centralized…