# Decentralized Identity Authentication with Auditability and Privacy
## 2 Background and Related Works
### Related Work  
Our work is the first to propose DID authentication protocols that achieve auditability and privacy. In the following, we discuss related works with similar properties. Blockstack [21] introduces a distributed namespace in which a binding of a name to a key can be published on a public blockchain. Similarly, CONIKS [22] supports name-to-key binding, and it provides publicly verifiable proof that the binding has been added to a public (centralized) log. The integrity of this log depends on a number of auditors  
Figure 1: Comparison between OAuth and DID authentication. that frequently check the log. This design is implemented in Google's Key Transparency (KT) [23]. These systems provide similar guarantees to those of a DID system, that is, full user control of the name-to-key binding and data transparency. However, like existing DIDs, they do not have the auditability property, as defined in this paper. [PERSON] et al. [24] introduced Ticket Transparency, an accountable single-sign-on system with a privacy-preserving public log. The system allows users to detect if an identity provider has signed a fraudulent ticket and if a ticket has been used to sign on to a service provider. The problem addressed by Ticket Transparency is similar to that of ours, but it is specific to existing single-sign-on systems with centralized identity providers. Our work focuses on DIDs in which users manage their own identities. Privacy Pass [25] is an anonymous user authentication scheme that provides users with the ability to create and sign cryptographically \"blinded\" tokens for services that require PoW authentication. Extending this, Facebook built a privacy-preserving logging scheme known as DIT [26], which addressed the constraints of implementing an anonymized logging infrastructure that involved mobile clients and additional requirements of lower latency. Though both addressed token anonymity achieving it while checking for token consistency could lead to a similar overhead to that of our privacy-preserving approach. Coconut [27] is a privacy-preserving verifiable credential scheme with a selective disclosure property supporting threshold credential issuances. The users can obtain a credential from the blockchain and authenticate with multiple services while being unlinkable across different usages. EL Passo [28] provides a privacy-preserving single-sign-on (SSO) system based on verifiable credentials that provide the same security guarantee as that of the traditional OAuth protocol without compromising on usability. The credential usage is similar to that of Coconut, and both use a PS signature [29] to implement a verifiable credential scheme. Unlike in our scheme, neither EL Passo nor Coconut aims to detect credential misuse. They can be seen as orthogonal to our work, and combining them with our solution could be a possibility for future work. WAVE [30] and Droplet [31] are decentralized authorization systems that aim to replace centralized solutions, such as OAuth. WAVE proposes novel cryptographic protocols for delegating access permissions without relying on trusted parties. It uses a secure log based on Google's Trillian [32] data store. The log can be efficiently audited to detect any forks in its history, similarly to CONIKS. In addition, WAVE supports user privacy by using a reverse-discoverable encryption scheme to encrypt authorization policies so that only users with appropriate permissions can see them. Droplet is very specific to the management of access to time-series data in an IoT environment. WAVE and Droplet are complementary to our work, since we focus on authentication instead of authorization. Going beyond authentication, SAMPL [33] proposes a blockchain-based system for auditing the user surveillance process. The auditability property targeted by this system is different from that in our definition, as it refers to the detection of non-compliance with the surveillance process--for example, when a user is being over-surveilled.