Related papers: Echomix: a Strong Anonymity System with Messaging
Due to the current standard of Security Credential Management System (SCMS) for Vehicle-to-Everything (V2X) communications using asymmetric cryptography, specifically Elliptic-Curve Cryptography (ECC), which may be vulnerable to quantum…
The safety of a quantum key distribution system relies on the fact that any eavesdropping attempt on the quantum channel creates errors in the transmission. For a given error rate, the amount of information that may have leaked to the…
We introduce what --if some kind of group action exists-- is a truly (information theoretically) safe cryptographic communication system: a protocol which provides \emph{zero} information to any passive adversary having full access to the…
The notion that collaborative machine learning can ensure privacy by just withholding the raw data is widely acknowledged to be flawed. Over the past seven years, the literature has revealed several privacy attacks that enable adversaries…
Homomorphic encryption is a very useful gradient protection technique used in privacy preserving federated learning. However, existing encrypted federated learning systems need a trusted third party to generate and distribute key pairs to…
This paper investigates artificial noise injection into the temporal and spatial dimensions of a legitimate wireless communication system to secure its transmissions from potential eavesdropping. We consider a multiple-input single-output…
Wireless communications empowered by Reconfigurable Intelligent (meta)Surfaces (RISs) are recently gaining remarkable research attention due to the increased system design flexibility offered by RISs for diverse functionalities. In this…
Privacy-preserving distributed processing has received considerable attention recently. The main purpose of these algorithms is to solve certain signal processing tasks over a network in a decentralised fashion without revealing…
Providing reliable and surreptitious communications is difficult in the presence of adaptive and resourceful state level censors. In this paper we introduce Tithonus, a framework that builds on the Bitcoin blockchain and network to provide…
Traffic analysis attacks can counteract end-to-end encryption and use leaked communication metadata to reveal information about communicating parties. With an ever-increasing amount of traffic by an ever-increasing number of networked…
Smart contracts are applications that execute on blockchains. Today they manage billions of dollars in value and motivate visionary plans for pervasive blockchain deployment. While smart contracts inherit the availability and other security…
In the era of social media and messaging applications, people are becoming increasingly aware of data privacy issues associated with such apps. Major messaging applications are moving towards end-to-end encryption (E2EE) to give their users…
A trusted electronic election system requires that all the involved information must go public, that is, it focuses not only on transparency but also privacy issues. In other words, each ballot should be counted anonymously, correctly, and…
Under the emerging network coding paradigm, intermediate nodes in the network are allowed not only to store and forward packets but also to process and mix different data flows. We propose a low-complexity cryptographic scheme that exploits…
Unsourced random access is a novel communication paradigm designed for handling a large number of uncoordinated users that sporadically transmit very short messages. Under this model, coded compressed sensing (CCS) has emerged as a…
Federated data analytics is a framework for distributed data analysis where a server compiles noisy responses from a group of distributed low-bandwidth user devices to estimate aggregate statistics. Two major challenges in this framework…
Biometric matching involves storing and processing sensitive user information. Maintaining the privacy of this data is thus a major challenge, and homomorphic encryption offers a possible solution. We propose a privacy-preserving…
Website fingerprinting (WF) attacks infer the websites visited by users from encrypted traffic in anonymous networks such as Tor. Existing deep learning methods achieve high accuracy under the single-tab assumption but degrade substantially…
Recent years have seen a strong uptick in both the prevalence and real-world consequences of false information spread through online platforms. At the same time, encrypted messaging systems such as WhatsApp, Signal, and Telegram, are…
Anonymous microblogging systems are known to be vulnerable to intersection attacks due to network churn. An adversary that monitors all communications can leverage the churn to learn who is publishing what with increasing confidence over…