Malicious Security for SCALES: Outsourced Computation with Ephemeral Servers
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 14928 LNCS, Page: 3-38
2024
- 1Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures1
- Readers1
Conference Paper Description
SCALES (Small Clients And Larger Ephemeral Servers) model is a recently proposed model for MPC (Acharya et al., TCC 2022). While the SCALES model offers several attractive features for practical large-scale MPC, the result of Acharya et al. only offered semi-honest secure protocols in this model. We present a new efficient SCALES protocol secure against malicious adversaries, for general Boolean circuits. We start with the base construction of Acharya et al. and design and use a suite of carefully defined building blocks that may be of independent interest. The resulting protocol is UC-secure without honest majority, with a CRS and bulletin-board as setups, and allows publicly identifying deviations from correct execution.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85202292191&origin=inward; http://dx.doi.org/10.1007/978-3-031-68400-5_1; https://link.springer.com/10.1007/978-3-031-68400-5_1; https://dx.doi.org/10.1007/978-3-031-68400-5_1; https://link.springer.com/chapter/10.1007/978-3-031-68400-5_1
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know