Efficiently Shuffling in Public

Parampalli, Udaya; Ramchen, Kim; Teague, Vanessa

doi:10.1007/978-3-642-30057-8_26

Cited by 6 publications

(3 citation statements)

References 27 publications

(34 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unfortunately, mix networks cannot be used in the described scenario to ensure unlinkability between players and their inputs due to several drawbacks. Most importantly, mixes need to be provided by different, independent parties [29]. This cannot be guaranteed in scenarios with a single, central service provider.…”

Section: A Approaches With Additional (Neutral) Instancesmentioning

confidence: 99%

Efficient Cloud-based Secret Shuffling via Homomorphic Encryption

Becher¹,

Strufe²

2020

Preprint

View full text Add to dashboard Cite

When working with joint collections of confidential data from multiple sources, e.g., in cloud-based multi-party computation scenarios, the ownership relation between data providers and their inputs itself is confidential information. Protecting data providers' privacy desires a function for secretly shuffling the data collection. We present the first efficient secure multi-party computation protocol for secret shuffling in scenarios with a central server. Based on a novel approach to random index distribution, our solution enables the randomization of the order of a sequence of encrypted data such that no observer can map between elements of the original sequence and the shuffled sequence with probability better than guessing. It allows for shuffling data encrypted under an additively homomorphic cryptosystem with constant round complexity and linear computational complexity. Being a general-purpose protocol, it is of relevance for a variety of practical use cases.

show abstract

Section: A Approaches With Additional (Neutral) Instancesmentioning

confidence: 99%

Efficient Cloud-based Secret Shuffling via Homomorphic Encryption

Becher¹,

Strufe²

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Another protocol for shuffling in public was proposed by Parampalli et al [38]. The protocol computes an obfuscated re-encryption shuffle based on the Damgård-Jurik cryptosystem [17].…”

Section: Shuffling In Publicmentioning

confidence: 99%

Compact Zero-Knowledge Proofs of Small Hamming Weight

Damgård

Luo

Oechsner

et al. 2018

Public-Key Cryptography – PKC 2018

View full text Add to dashboard Cite

We introduce a new technique that allows to give a zeroknowledge proof that a committed vector has Hamming weight bounded by a given constant. The proof has unconditional soundness and is very compact: It has size independent of the length of the committed string, and for large fields, it has size corresponding to a constant number of commitments. We show five applications of the technique that play on a common theme, namely that our proof allows us to get malicious security at small overhead compared to semi-honest security: (1) actively secure k-out-of-n OT from black-box use of 1-out-of-2 OT, (2) separable accountable ring signatures, (3) more efficient preprocessing for the TinyTable secure two-party computation protocol, (4) mixing with public verifiability, and (5) PIR with security against a malicious client.

show abstract

“…First, shufflebased systems defend against passive traffic analysis attacks by messing up the order of user messages to hide corresponding message senders. In practice, either statistical shuffles [18] or cryptographic shuffles [19], [20] is used. To guarantee that messages are shuffled sufficiently (i.e., integrity), statistical shuffle assumes that the majority of machines for message shuffles are trustworthy [7], [21], and cryptographic shuffle requires users to verify the integrity cryptographically [16], [22].…”

mentioning

confidence: 99%

DAENet: Making Strong Anonymity Scale in a Fully Decentralized Network

Shen

Jiang

et al. 2022

IEEE Trans. Dependable and Secure Comput.

View full text Add to dashboard Cite

Traditional anonymous networks (e.g., Tor) are vulnerable to traffic analysis attacks that monitor the whole network traffic to determine which users are communicating. To preserve user anonymity against traffic analysis attacks, the emerging mix networks mess up the order of packets through a set of centralized and explicit shuffling nodes. However, this centralized design of mix networks is insecure against targeted DoS attacks that can completely block these shuffling nodes. In this article, we present DAENet, an efficient mix network that resists both targeted DoS attacks and traffic analysis attacks with a new abstraction called Stealthy Peer-to-Peer (P2P) Network. The stealthy P2P network effectively hides the shuffling nodes used in a routing path into the whole network, such that adversaries cannot distinguish specific shuffling nodes and conduct targeted DoS attacks to block these nodes. In addition, to handle traffic analysis attacks, we leverage the confidentiality and integrity protection of Intel SGX to ensure trustworthy packet shuffles at each distributed host and use multiple routing paths to prevent adversaries from tracking and revealing user identities. We show that our system is scalable with moderate latency (2.2s) when running in a cluster of 10,000 participants and is robust in the case of machine failures, making it an attractive new design for decentralized anonymous communication. DAENet 's code is released on https://github.com/hku-systems/DAENet.

show abstract

Efficiently Shuffling in Public

Cited by 6 publications

References 27 publications

Efficient Cloud-based Secret Shuffling via Homomorphic Encryption

Efficient Cloud-based Secret Shuffling via Homomorphic Encryption

Compact Zero-Knowledge Proofs of Small Hamming Weight

DAENet: Making Strong Anonymity Scale in a Fully Decentralized Network

Contact Info

Product

Resources

About