Privacy-preserving matrix factorization

Nikolaenko, Valeria; Ioannidis, Stratis; Weinsberg, Udi; Joye, Marc; Taft, Nina; Boneh, Dan

doi:10.1145/2508859.2516751

Cited by 234 publications

(211 citation statements)

References 50 publications

Supporting

Mentioning

211

Contrasting

Order By: Relevance

“…For his outputs, he is given a mapping that allows him to decrypt the output keys into plain output values. For Yao's garbled circuits protocol we use the following optimizations and instantiations that are implemented in FastGC [24] (which is used in many recent works such as [22,23,21,45,46]) and VMCrypt [38]: For OT we use OT extensions of [26] with the OT protocol of [42] for the base OTs. For garbled circuits we use free XOR gates [34], garbled row reduction [43,51], and pipelining [24].…”

Section: Garbled Circuitsmentioning

confidence: 99%

“…A number of protocols compete for the best performance in this model. Recently, the garbled circuit implementation FastGC [24] has been used in several privacy-preserving applications, including [22,23,21,45,46], but still garbled circuits have some inherent limitations, e.g., due to the large circuit size of some functionalities such as multiplication. In this paper we propose a different approach.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Automatic Protocol Selection in Secure Two-Party Computations

Kerschbaum

Schneider

Schröpfer

2014

Applied Cryptography and Network Security

View full text Add to dashboard Cite

Abstract. Performance of secure computation is still often an obstacle to its practical adaption. There are different protocols for secure computation that compete for the best performance. In this paper we propose automatic protocol selection which selects a protocol for each operation resulting in a mix with the best performance so far. Based on an elaborate performance model, we propose an optimization algorithm and an efficient heuristic for this selection problem. We show that our mixed protocols achieve the best performance on a set of use cases. Furthermore, our results underpin that the selection problem is so complicated and large in size, that a programmer is unlikely to manually make the optimal selection. Our proposed algorithms nevertheless can be integrated into a compiler in order to yield the best (or near-optimal) performance.

show abstract

Section: Garbled Circuitsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic Protocol Selection in Secure Two-Party Computations

Kerschbaum

Schneider

Schröpfer

2014

Applied Cryptography and Network Security

View full text Add to dashboard Cite

show abstract

“…The cryptographic solutions (e.g. [1], [10], [23], [28], [32]) often aim at securing the procedure of underlying recommender protocols, namely they do not consider the information leakage in the outputs. In this category, a typical method is to employ somewhat homomorphic encryption scheme and let all computations be done in encrypted form.…”

Section: A Related Workmentioning

confidence: 99%

“…Moreover, many solutions (e.g. [23], [32]) introduce additional semi-trusted servers which are difficult to be instantiated in reality. The data-obfuscation solutions (e.g.…”

Section: A Related Workmentioning

confidence: 99%

Privacy-Preserving Friendship-Based Recommender Systems

Tang

Wang

2018

IEEE Trans. Dependable and Secure Comput.

View full text Add to dashboard Cite

Privacy-preserving recommender systems have been an active research topic for many years. However, until today, it is still a challenge to design an efficient solution without involving a fully trusted third party or multiple semitrusted third parties. The key obstacle is the large underlying user populations (i.e. huge input size) in the systems. In this paper, we revisit the concept of friendship-based recommender systems, proposed by Jeckmans et al. and Tang and Wang. These solutions are very promising because recommendations are computed based on inputs from a very small subset of the overall user population (precisely, a user's friends and some randomly chosen strangers). We first clarify the single prediction protocol and Top-n protocol by Tang and Wang, by correcting some flaws and improving the efficiency of the single prediction protocol. We then design a decentralized single protocol by getting rid of the semi-honest service provider. In order to validate the designed protocols, we crawl Twitter and construct two datasets (FMT and 10-FMT) which are equipped with auxiliary friendship information. Based on 10-FMT and MovieLens 100k dataset with simulated friendships, we show that even if our protocols use a very small subset of the datasets, their accuracy can still be equal to or better than some baseline algorithm. Based on these datasets, we further demonstrate that the outputs of our protocols leak very small amount of information of the inputs, and the leakage decreases when the input size increases. We finally show that he single prediction protocol is quite efficient but the Top-n is not. However, we observe that the efficiency of the Top-n protocol can be dramatically improved if we slightly relax the desired security guarantee.

show abstract

“…It is argued in [85] that it is paramount for privacy that users keep their data (e.g. ratings and user factors) local.…”

Section: Contributionsmentioning

confidence: 99%

Gossip-Based Machine Learning in Fully Distributed Environments

Hegedűs

View full text Add to dashboard Cite

Privacy-preserving matrix factorization

Cited by 234 publications

References 50 publications

Automatic Protocol Selection in Secure Two-Party Computations

Automatic Protocol Selection in Secure Two-Party Computations

Privacy-Preserving Friendship-Based Recommender Systems

Gossip-Based Machine Learning in Fully Distributed Environments

Contact Info

Product

Resources

About