Introducing Accountability to Anonymity Networks

Many anonymous communication (AC) networks rely on routing traffic through proxy nodes to obfuscate the originator of the traffic. Without an accountability mechanism, exit proxy nodes risk sanctions by law enforcement if users commit illegal actions through the AC network. We present BackRef, a generic mechanism for AC networks that provides practical repudiation for the proxy nodes by tracing back the selected outbound traffic to the predecessor node (but not in the forward direction) through a cryptographically verifiable chain. It also provides an option for full (or partial) traceability back to the entry node or even to the corresponding user when all intermediate nodes are cooperating. Moreover, to maintain a good balance between anonymity and accountability, the protocol incorporates whitelist directories at exit proxy nodes. BackRef offers improved deployability over the related work, and introduces a novel concept of pseudonymous signatures that may be of independent interest. We exemplify the utility of BackRef by integrating it into the onion routing (OR) protocol, and examine its deployability by considering several system-level aspects. We also present the security definitions for the BackRef system (namely, anonymity, backward traceability, no forward traceability, and no false accusation) and conduct a formal security analysis of the OR protocol with BackRef using ProVerif, an automated cryptographic protocol verifier, establishing the aforementioned security properties against a strong adversarial model

A-MAKE: an efficient, anonymous and accountable authentication framework for WMNs

In this paper, we propose a framework, named as A-MAKE, which efficiently provides security, privacy, and accountability for communications in wireless mesh networks. More specifically, the framework provides an anonymous mutual authentication protocol whereby legitimate users can connect to network from anywhere without being identified or tracked. No single party (e.g., network operator) can violate the privacy of a user, which is provided in our framework in the strongest sense. Our framework utilizes group signatures, where the private key and the credentials of the users are generated through a secure three-party protocol. User accountability is implemented via user revocation protocol that can be executed by two semitrusted authorities, one of which is the network operator. The assumptions about the trust level of the network operator are relaxed. Our framework makes use of much more efficient signature generation and verification algorithms in terms of computation complexity than their counterparts in literature, where signature size is comparable to the shortest signatures proposed for similar purposes so far

IDEA-DAC: Integrity-Driven Editing for Accountable Decentralized Anonymous Credentials via ZK-JSON

Decentralized Anonymous Credential (DAC) systems are increasingly relevant, especially when enhancing revocation mechanisms in the face of complex traceability challenges. This paper introduces IDEA-DAC, a paradigm shift from the conventional revoke-and-reissue methods, promoting direct and Integrity-Driven Editing (IDE) for Accountable DACs, which results in better integrity accountability, traceability, and system simplicity. We further incorporate an Edit-bound Conformity Check that ensures tailored integrity standards during credential amendments using R1CS-based ZK-SNARKs. Delving deeper, we propose ZK-JSON, a unique R1CS circuit design tailored for IDE over generic JSON documents. This design imposes strictly $O(N)$ rank-1 constraints for variable-length JSON documents of up to $N$ bytes in length, encompassing serialization, encryption, and edit-bound conformity checks. Additionally, our circuits only necessitate a one-time compilation, setup, and smart contract deployment for homogeneous JSON documents up to a specified size. While preserving core DAC features such as selective disclosure, anonymity, and predicate provability, IDEA-DAC achieves precise data modification checks without revealing private content, ensuring only authorized edits are permitted. In summary, IDEA-DAC offers an enhanced methodology for large-scale JSON-formatted credential systems, setting a new standard in decentralized identity management efficiency and precision

PAPR: Publicly Auditable Privacy Revocation for Anonymous Credentials

We study the notion of anonymous credentials with Publicly Auditable Privacy Revocation (PAPR). PAPR credentials simultaneously provide conditional user privacy and auditable privacy revocation. The first property implies that users keep their identity private when authenticating unless and until an appointed authority requests to revoke this privacy, retroactively. The second property enforces that auditors can verify whether or not this authority has revoked privacy from an issued credential (i.e. learned the identity of the user who owns that credential), holding the authority accountable. In other words, the second property enriches conditionally anonymous credential systems with transparency by design, effectively discouraging such systems from being used for mass surveillance. In this work, we introduce the notion of a PAPR anonymous credential scheme, formalize it as an ideal functionality, and present constructions that are provably secure under standard assumptions in the Universal Composability framework. The core tool in our PAPR construction is a mechanism for randomly selecting an anonymous committee which users secret share their identity information towards, while hiding the identities of the committee members from the authority. As a consequence, in order to initiate the revocation process for a given credential, the authority is forced to post a request on a public bulletin board used as a broadcast channel to contact the anonymous committee that holds the keys needed to decrypt the identity connected to the credential. This mechanism makes the user de-anonymization publicly auditable

ZEBRA: SNARK-based Anonymous Credentials for Practical, Private and Accountable On-chain Access Control

Restricting access to certified users is not only desirable for many blockchain applications, it is also legally mandated for decentralized finance (DeFi) applications to counter malicious actors. Existing solutions, however, are either (i) non-private, i.e., they reveal the link between users and their wallets to the authority granting credentials, or (ii) they introduce additional trust assumptions by relying on a decentralized oracle to verify anonymous credentials (ACs). To remove additional trust in the latter approach, we propose verifying credentials on-chain in this work. We find that this approach has impractical costs with prior AC schemes, and propose a new AC scheme ZEBRA that crucially relies on zkSNARKs to provide efficient on-chain verification for the first time. In addition to the standard unlinkability property that provides privacy for users, ZEBRA also supports auditability, revocation, traceability, and theft detection, which adds accountability for malicious users and convenience for honest users to our access control solution. Even with these properties, ZEBRA reduces the gas cost incurred on the Ethereum Virtual Machine (EVM) by 14.3x when compared to Coconut [NDSS 2019], the state-of-the-art AC scheme for blockchains that only provides unlinkability. This improvement translates to a reduction in transaction fees from 176 USD to 12 USD on Ethereum in May 2023. Since 12 USD is still high for most applications, ZEBRA further drives down credential verification costs through batched verification. For a batch of 512 layer-1 and layer-2 wallets, the transaction fee on Ethereum is reduced to just 0.44 USD and 0.02 USD, respectively, which is comparable to the minimum transaction costs on Ethereum

A Real World Identity Management System with Master Secret Revocation

Cybersecurity mechanisms have become increasingly important as online and offline worlds converge. Strong authentication and accountability are key tools for dealing with online attacks, and we would like to realize them through a token-based, centralized identity management system. In this report, we present a privacy-preserving group of protocols comprising a unique per user digital identity card, with which its owner is able to authenticate himself, prove possession of attributes, register himself to multiple online organizations (anonymously or not) and provide proof of membership. Unlike existing credential-based identity management systems, this card is revocable, i.e., its legal owner may invalidate it if physically lost, and still recover its content and registrations into a new credential. This card will protect an honest individual's anonymity when applicable as well as ensure his activity is known only to appropriate users

Anonymous reputation based reservations in e-commerce (AMNESIC)

Online reservation systems have grown over the last recent years to facilitate the purchase of goods and services. Generally, reservation systems require that customers provide some personal data to make a reservation effective. With this data, service providers can check the consumer history and decide if the user is trustable enough to get the reserve. Although the reputation of a user is a good metric to implement the access control of the system, providing personal and sensitive data to the system presents high privacy risks, since the interests of a user are totally known and tracked by an external entity. In this paper we design an anonymous reservation protocol that uses reputations to profile the users and control their access to the offered services, but at the same time it preserves their privacy not only from the seller but the service provider

A Secure and Privacy-Preserving Targeted Ad-System

Thanks to its low product-promotion cost and its efficiency, targeted online advertising has become very popular. Unfortunately, being profile-based, online advertising methods violate consumers' privacy, which has engendered resistance to the ads. However, protecting privacy through anonymity seems to encourage click-fraud. In this paper, we define consumer's privacy and present a privacy-preserving, targeted ad system (PPOAd) which is resistant towards click fraud. Our scheme is structured to provide financial incentives to to all entities involved