Stadium

Abstract

Private communication over the Internet remains a challenging problem. Even if messages are encrypted, it is hard to deliver them without revealing metadata about which pairs of users are communicating. Scalable anonymity systems, such as Tor, are susceptible to traffic analysis attacks that leak metadata. In contrast, the largest-scale systems with metadata privacy require passing all messages through a small number of providers, requiring a high operational cost for each provider and limiting their deployability in practice. This paper presents Stadium, a point-to-point messaging system that provides metadata and data privacy while scaling its work efficiently across hundreds of low-cost providers operated by different organizations. Much like Vuvuzela, the current largest-scale metadata-private system, Stadium achieves its provable guarantees through differential privacy and the addition of noisy cover traffic. The key challenge in Stadium is limiting the information revealed from the many observable traffic links of a highly distributed system, without requiring an overwhelming amount of noise. To solve this challenge, Stadium introduces techniques for distributed noise generation and differentially private routing as well as a verifiable parallel mixnet design where the servers collaboratively check that others follow the protocol. We show that Stadium can scale to support 4× more users than Vuvuzela using servers that cost an order of magnitude less to operate than Vuvuzela nodes.

Fighting Fake News in Encrypted Messaging with the Fuzzy Anonymous Complaint Tally System (FACTS)

“…However, some existing EEMS attempt to also obscure this metadata in transmitting messages, so that the server does not learn both sender and recipient of any message. This can trivially be accomplished by foregoing a central server and doing peer-to-peer communication (note that FACTS may still be useful as a central complaint repository); or using more sophisticated cryptography to hide metadata [6], [10], [41].…”

AOT: Anonymization by Oblivious Transfer

“…Moreover, in Vuvuzela, the adversary can distinguish whether a receiver is participating in a dialing or conversation protocol, whereas in AOT the adversary cannot make this distinction. Stadium [65] adds horizontal scalability and verifiable mixing to Vuvuzela. Deaddrops and AOT's message tags (See Section 4.1) are similar to the rendezvous hash value of the UDM protocol of Chaum et al [17].…”

“…We compare design features and security and efficiency properties of AOT with those of selected other ACSs: original mixnet (OM) [12], cMix [16], Riffle [43], Stadium [65], Vuvuzela [66], and Loopix [55]. Table 1 summarizes the comparison.…”

“…Comparison of AOT with selected ACSs with respect to design characteristics, security, and efficiency. The comparison set comprises original mixnet (OM) [12], cMix [16], Riffle [43], Stadium [65], Vuvuzela [66], and Loopix [55].…”

RPM: Robust Anonymity at Scale

“…There are by now millions of users using the Tor network [27,28] to break the link between their identities and their messages/packets. As the solutions like Tor network suffer from traffic analysis attacks [11,31,38], anonymous communication becomes an active research area and many works [1,3,29,42,43,47,52,53] aim at providing anonymous communication services efficiently. This work explores the solutions of anonymous communication with the help of secure multi-party computation (MPC).…”