PSI
BuRR
PSI | BuRR | |
---|---|---|
3 | 1 | |
125 | 34 | |
0.0% | - | |
5.2 | 3.8 | |
25 days ago | about 1 month ago | |
C++ | C++ | |
Apache License 2.0 | Apache License 2.0 |
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PSI
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Can a new form of cryptography solve the internet’s privacy problem?
There are other techniques that aren't generally included in the "Zero Knowledge Proofs" set of techniques that are perhaps more practical for general development.
For example, I fine private set intersection[1] as implemented by OpenMined a really useful primative a bunch of privacy enhancing applications can be built on top of.
My colleagues and I recently published a pre-print[2] showing how to use this for sharing locations you and another person have had in common, without being able to see other locations. The paper talks about a social network built around this but I also think there are useful applications in things like real-world games (scavenger hunts etc)
[1] https://github.com/OpenMined/PSI/blob/master/private_set_int...
[2] https://arxiv.org/abs/2210.01927
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Ask HN: What are some 'cool' but obscure data structures you know about?
I came here to say Golomb compressed sets except now I see it's part of the question!
They are used by default in the OpenMined implementation of Private Set Intersection[1] - a multi-party computation technique.
[1] https://github.com/OpenMined/PSI/blob/master/private_set_int...
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Is there a Private Set Intersection protocol where the server learns the length of the intersection?
I was using OpenMinded/PSI exploring some PSI implementations, but I would like a way for the server to know the intersection size. Say Signal wants to calculate the average number of users from one person's address book (or whatever).
BuRR
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Ask HN: What are some 'cool' but obscure data structures you know about?
If you enjoyed XOR filters, you might also like ribbon filters, something that I had the pleasure of working on last year. They share the basic idea of using a system of linear equations, but instead of considering 3 random positions per key, the positions to probe are narrowly concentrated along a ribbon with a typical width of 64. This makes them far more cache-efficient to construct and query.
By purposefully overloading the data structure by a few per cent and bumping those items that cannot be inserted as a result of this overloading to the next layer (making this a recursive data structure), we can achieve almost arbitrarily small space overheads: <1% is no problem for the fast configurations, and <0.1% overhead with around 50% extra runtime cost. This compares to around 10% for XOR filters and ≥ 44% for Bloom filters.
In fact, I'm going to present them at a conference on Monday - the paper is already out: https://drops.dagstuhl.de/opus/volltexte/2022/16538/pdf/LIPI... and the implementation is at https://github.com/lorenzhs/BuRR/. I hope this isn't too much self-promotion for HN, but I'm super hyped about this :)
What are some alternatives?
ctrie-java - Java implementation of a concurrent trie
Caffeine - A high performance caching library for Java
AspNetCoreDiagnosticScenarios - This repository has examples of broken patterns in ASP.NET Core applications
bloom_cpp - Bloom Filter implemention in C++
t-digest - A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means
multiversion-concurrency-contro
cheerp-meta - Cheerp - a C/C++ compiler for Web applications - compiles to WebAssembly and JavaScript
CPython - The Python programming language
swift - the multiparty transport protocol (aka "TCP with swarming" or "BitTorrent at the transport layer")
RVS_Generic_Swift_Toolbox - A Collection Of Various Swift Tools, Like Extensions and Utilities
pvfmm - A parallel kernel-independent FMM library for particle and volume potentials
pyroscope - Continuous Profiling Platform. Debug performance issues down to a single line of code [Moved to: https://github.com/grafana/pyroscope]