rhindi

6 ms·

1.
by rhindi 2y ago
They use BFV, which is an FHE scheme allowing a limited number of fast additions and multiplications (enough for their use case). Zama uses TFHE, which allows any operation (eg comparisons) with unlimited depth. So if you only need add&#x2F
2.
by rhindi 2y ago
There are some non-ML based approaches for ultra low field MRI that are starting to work: https://drive.google.com/file/d/1m7K1W--UOUecDPlm7KqFYzfkoew... . You can still add AI on top of course, but at least you g
3.
A solution to A16Z Nakamoto challenge on "Compliant Programmable Privacy"(zama.ai)
43 points by rhindi 3y ago|3 comments
4.
by rhindi 3y ago
FHE in general is efficient enough for many applications now. You can see some benchmarks here: https://docs.zama.ai/tfhe-rs/getting-started/benchmarks
5.
FhEVM whitepaper (homomorphic encryption for blockchain) [pdf](github.com)
3 points by rhindi 3y ago|0 comments
6.
by rhindi 3y ago
We are planning several other blog posts to explain all the details. In the meantime if you want a good introduction to the FHE scheme we use behind the scene, you can take a look here: https://www.zama.ai/post/tfhe-dee
7.
by rhindi 4y ago
Multiple teams are working on FHE smart contracts, including us, so it’s definitely happening. Adding ZK to the mix would be awesome for scalability and indeed to avoid replicating the FHE computation
8.
by rhindi 4y ago
It’s much much faster now, and performance is improving 10x every couple of year. With the current trend, FHE will be applicable to 80% of usecases by 2025
9.
Concrete: Homomorphic encryption library for non-cryptographers(github.com)
1 points by rhindi 4y ago|0 comments
10.
Motif: Programmable Blogs for Developers(motif.land)
1 points by rhindi 5y ago|0 comments
11.
NumPy Homomorphic Encryption Library(medium.com)
1 points by rhindi 5y ago|0 comments
12.
String Search with Homomorphic Encryption(medium.com)
1 points by rhindi 5y ago|0 comments
13.
by rhindi 5y ago
Have you considered using FHE for analyzing the photos encrypted?
14.
by rhindi 5y ago
Yes, in practice however it makes a difference. Consider for example computing the ReLu function for a neural network: - With boolean circuits you need to run dozens of boolean gates, which means a lot of underlying crypto ops. Works but ex
15.
by rhindi 5y ago
It's really great to see more big companies getting into this game, ease of adoption is really the key here. When it comes to FHE, there are 3 underlying paradigms you can target with compilers: 1. boolean circuits, where you represent
16.
by rhindi 5y ago
If it helps, we did a mini site to explain FHE: https://6min.zama.ai
17.
by rhindi 5y ago
8 bit is definitely doable today, fast There are basically 2 strategies: - do fast operations, with a limit on how many you can do. This is called Leveled Homomorphic Encryption, with CKKS being the most popular scheme. Microsoft open sourc
18.
by rhindi 5y ago
Homomorphic encryption, which enables you to process data without decrypting it. Would solve privacy / data security issues around sending data to be processed in the cloud
19.
by rhindi 6y ago
Just dual license your code with an AGPL and commercial license. Proprietary software companies hate AGPL, and won’t take the risk to use it, instead preferring to pay your commercial license. MongoDB does that very successfully!
20.
by rhindi 6y ago
Nice overview! A few comments: - homomorphic encryption is much much faster now, so the latency argument against won’t hold much longer - with multi-key FHE, you could replace MPC, without the integration complexity and increased bandwidth
21.
by rhindi 6y ago
Homomorphic encryption and the trend of making everything end to end encrypted online. Puts an end to surveillance, data theft, and complex regulatory frameworks. Makes people feel safe about using online services, and makes companies feel
22.
by rhindi 6y ago
Yes, turns out you can convert ciphertexts from one scheme to another, so you can go back and forth between them depending on what type of computation you are trying to do. However the cost of transciphering is high, so in practice it doesn
23.
by rhindi 6y ago
The server doesn’t need the decryption key, ever. Thats the whole point in fact. FHE is end to end encryption for compute. However there is sometimes a public key used, called an evaluation key.
24.
by rhindi 6y ago
All FHE schemes today add tiny random noise to the ciphertext so that encrypting the same data twice give different results. The noise is then kept to a nominal level as you compute homomorphically using a special operation called bootstrap
25.
by rhindi 6y ago
I suggest looking at TFHE and SEAL for starters
26.
by rhindi 6y ago
You have formulas to calculate the security level given a threat model, so the compiler could in theory do it automatically. Just specify that you wants 128 bits of security or whatever, and it will do the rest.
27.
by rhindi 6y ago
All modern FHE is lattice based, so pretty strong if you chose the right parameters. But of course if you dont chose secure parameters.. well, it wont be secure :) There are tools to measure the security level of FHE schemes: https:/&
28.
by rhindi 6y ago
There are two main approaches to FHE: homomorphic boolean circuits and homomorphic numerical processing. In the former (eg Cingulata), you convert a program into a boolean circuit, and evaluate each gate homomorphically. While this is gener
29.
by rhindi 7y ago
Actually homomorphic encryption always ends up running as slow as the worse case, so you can’t do a sidechannel attack by looking at the computation time.
30.
by rhindi 7y ago
Yes, all the fully homomorphic schemes are lattice based and thus thought to be quantum resistant

More ›