Anonymous Tokens with Private Metadata Bit

We present a cryptographic construction for anonymous tokens with private metadata bit, called PMBTokens. This primitive enables an issuer to provide a user with a lightweight, single-use anonymous trust token that can embed a single private bit, which is accessible only to the party who holds the secret authority key and is private with respect to anyone else. Our construction generalizes and extends the functionality of Privacy Pass (PETS’18) with this private metadata bit capability. It is based on the DDH and CTDH assumptions in the random oracle model and provides unforgeability, unlinkability, and privacy for the metadata bit. Both Privacy Pass and PMBTokens rely on non-interactive zero-knowledge proofs (NIZKs). We present new techniques to remove the need for NIZKs, while still achieving unlinkability. We implement our constructions and we report their efficiency costs

Publicly verifiable anonymous tokens with private metadata bit

We present a new construction for publicly verifiable anonymous tokens with private metadata. This primitive enables an issuer to generate an anonymous authentication token for a user while embedding a single private metadata bit. The token can be publicly verified, while the value of the private metadata is only accessible to the party holding the secret issuing key and remains hidden to any other party, even to the user. The security properties of this primitive also include unforgeability, which guarantees that only the issuer can generate new valid tokens, and unlinkability that guarantees that tokens issued with the same private metadata bit are indistinguishable. Our anonymous tokens scheme builds on the top of blind Schnorr signatures. We analyze its security in the algebraic group model and prove its security under the modified ROS assumption, one-more discrete logarithm, and decisional Diffie-Hellman assumptions

A Forensically Sound Adversary Model for Mobile Devices

In this paper, we propose an adversary model to facilitate forensic investigations of mobile devices (e.g. Android, iOS and Windows smartphones) that can be readily adapted to the latest mobile device technologies. This is essential given the ongoing and rapidly changing nature of mobile device technologies. An integral principle and significant constraint upon forensic practitioners is that of forensic soundness. Our adversary model specifically considers and integrates the constraints of forensic soundness on the adversary, in our case, a forensic practitioner. One construction of the adversary model is an evidence collection and analysis methodology for Android devices. Using the methodology with six popular cloud apps, we were successful in extracting various information of forensic interest in both the external and internal storage of the mobile device

DESIRE: A Third Way for a European Exposure Notification System Leveraging the best of centralized and decentralized systems

This document presents an evolution of the ROBERT protocol that decentralizes most of its operations on the mobile devices. DESIRE is based on the same architecture than ROBERT but implements major privacy improvements. In particular, it introduces the concept of Private Encounter Tokens, that are secret and cryptographically generated, to encode encounters. In the DESIRE protocol, the temporary Identifiers that are broadcast on the Bluetooth interfaces are generated by the mobile devices providing more control to the users about which ones to disclose. The role of the server is merely to match PETs generated by diagnosed users with the PETs provided by requesting users. It stores minimal pseudonymous data. Finally, all data that are stored on the server are encrypted using keys that are stored on the mobile devices, protecting against data breach on the server. All these modifications improve the privacy of the scheme against malicious users and authority. However, as in the first version of ROBERT, risk scores and notifications are still managed and controlled by the server of the health authority, which provides high robustness, flexibility, and efficacy

Alpenhorn: Bootstrapping Secure Communication without Leaking Metadata

Alpenhorn is the first system for initiating an encrypted connection between two users that provides strong privacy and forward secrecy guarantees for metadata (i.e., information about which users connected to each other) and that does not require out-of-band communication other than knowing the other user's Alpenhorn username (email address). This resolves a significant shortcoming in all prior works on private messaging, which assume an out-of-band key distribution mechanism. Alpenhorn's design builds on three ideas. First, Alpenhorn provides each user with an address book of friends that the user can call to establish a connection. Second, when a user adds a friend for the first time, Alpenhorn ensures the adversary does not learn the friend's identity, by using identity-based encryption in a novel wayto privately determine the friend's public key. Finally, when calling a friend, Alpenhorn ensures forward secrecy of metadata by storing pairwise shared secrets in friends' address books, and evolving them over time, using a new keywheel construction. Alpenhorn relies on a number of servers, but operates in an anytrust model, requiring just one of the servers to be honest. We implemented a prototype of Alpenhorn, and integrated it into the Vuvuzela private messaging system (which did not previously provide privacy or forward secrecy of metadata when initiating conversations). Experimental results show that Alpenhorn can scale to many users, supporting 10 million users on three Alpenhorn servers with an average call latency of 150 seconds and a client bandwidth overhead of 3.7 KB/sec

Hydra: practical metadata security for contact discovery, messaging, and voice calls

Protecting communications’ metadata can be as important as protecting their content, i.e., recognizing someone contacting a medical service may already allow to infer sensitive information. There are numerous proposals to implement anonymous communications, yet none provides it in a strong (but feasible) threat model in an efficient way. We propose Hydra, an anonymity system that is able to efficiently provide metadata security for a wide variety of applications. Main idea is to use latency-aware, padded, and onion-encrypted circuits even for connectionless applications. This allows to implement strong metadata security for contact discovery and text-based messages with relatively low latency. Furthermore, circuits can be upgraded to support voice calls, real-time chat sessions, and file transfers - with slightly reduced anonymity in presence of global observers. We evaluate Hydra using an analytical model as well as call simulations. Compared to other systems for text-based messaging, Hydra is able to decrease end-to-end latencies by an order of magnitude without degrading anonymity. Using a dataset generated by performing latency measurements in the Tor network, we further show that Hydra is able to support anonymous voice calls with acceptable quality of service in real scenarios. A first prototype of Hydra is published as open source

Anonymous Tokens with Public Metadata and Applications to Private Contact Tracing

Anonymous single-use tokens have seen recent applications in private Internet browsing and anonymous statistics collection. We develop new schemes in order to include public metadata such as expiration dates for tokens. This inclusion enables planned mass revocation of tokens without distributing new keys, which for natural instantiations can give 77 % and 90 % amortized traffic savings compared to Privacy Pass (Davidson et al., 2018) and DIT: De-Identified Authenticated Telemetry at Scale (Huang et al., 2021), respectively. By transforming the public key, we are able to append public metadata to several existing protocols essentially without increasing computation or communication. Additional contributions include expanded definitions, a more complete framework for anonymous single-use tokens and a description of how anonymous tokens can improve the privacy in dp3t-like digital contact tracing applications. We also extend the protocol to create efficient and conceptually simple tokens with both public and private metadata, and tokens with public metadata and public verifiability from pairings

InShopnito: an advanced yet privacy-friendly mobile shopping application

Mobile Shopping Applications (MSAs) are rapidly gaining popularity. They enhance the shopping experience, by offering customized recommendations or incorporating customer loyalty programs. Although MSAs are quite effective at attracting new customers and binding existing ones to a retailer's services, existing MSAs have several shortcomings. The data collection practices involved in MSAs and the lack of transparency thereof are important concerns for many customers. This paper presents inShopnito, a privacy-preserving mobile shopping application. All transactions made in inShopnito are unlinkable and anonymous. However, the system still offers the expected features from a modern MSA. Customers can take part in loyalty programs and earn or spend loyalty points and electronic vouchers. Furthermore, the MSA can suggest personalized recommendations even though the retailer cannot construct rich customer profiles. These profiles are managed on the smartphone and can be partially disclosed in order to get better, customized recommendations. Finally, we present an implementation called inShopnito, of which the security and performance is analyzed. In doing so, we show that it is possible to have a privacy-preserving MSA without having to sacrifice practicality