Update README

README.md

@@ -1,14 +1,15 @@
-# Efficient and Secure k-NN Classification from Improved Data-Oblivious Programs and Homomorphic Encryption
+# ppknn
 
 [![Rust](https://github.com/kc1212/ppknn/actions/workflows/rust.yml/badge.svg)](https://github.com/kc1212/ppknn/actions/workflows/rust.yml)
 
-This is the code used in the paper "[Efficient and Secure k-NN Classification from Improved Data-Oblivious Programs and Homomorphic Encryption](https://eprint.iacr.org/2023/852)" by Kelong Cong, Robin Geelen, Jiayi Kang and Jeongeun Park.
+This is the code used in the paper "[Revisiting Oblivious Top-k Selection with Applications to Secure k-NN Classification](https://eprint.iacr.org/2023/852)" by Kelong Cong, Robin Geelen, Jiayi Kang and Jeongeun Park.
 
 *WARNING:*
 
 This is proof-of-concept implementation. It may contain bugs and security issues. Please do not use in production systems.
 
 ## Building and testing
+Only tested on x84-64, on Linux.
 ```
 cargo build --release
 cargo test --release # might take a few minutes
@@ -28,30 +29,3 @@ and should not contain values higher than 255.
 For running longer experiments,
 especially to reproduce the results from the paper,
 see the scripts `scripts/bench-cancer.sh` and `scripts/bench-mnist.sh`.
-
-## Internals
-
-This is an improvement over the k-NN
-paper by Zuber and Sirdey [0].
-We use Batcher's odd-even sorting network
-as described by Knuth [1].
-The algorithm is optimized to output `k`
-sorted elements instead of `n`,
-where `n` is the length of the array.
-This modification results in much fewer comparison,
-which is expensive to do homomorphically,
-when `k` is low.
-
-The homomorphic encryption scheme we use is TFHE [2]
-from the [tfhe-rs](tfhe.rs) library.
-Some internal data structures are not exposed
-by default in tfhe-rs, so we use a
-[forked version](https://github.com/kc1212/tfhe-rs/tree/expose-sk).
-
-## References
-
-[0] https://petsymposium.org/popets/2021/popets-2021-0020.pdf
-
-[1] The Art of Computer Programming, Vol. 3 Sorting and Searching, Donald E. Knuth
-
-[2] https://eprint.iacr.org/2018/421.pdf