Polar Coded Merkle Tree: Improved Detection of Data Availability Attacks in Blockchain Systems
This addresses a vulnerability for light nodes in blockchain systems, offering an incremental improvement over existing coding schemes.
The paper tackles the problem of data availability attacks in blockchain systems by proposing a Polar Coded Merkle Tree with Sampling-Efficient Freezing polar codes, which improves detection for large block sizes compared to previous methods like LDPC and 2-D Reed Solomon codes.
Light nodes in blockchain systems are known to be vulnerable to data availability (DA) attacks where they accept an invalid block with unavailable portions. Previous works have used LDPC and 2-D Reed Solomon (2D-RS) codes with Merkle Trees to mitigate DA attacks. While these codes have demonstrated improved performance across a variety of metrics such as DA detection probability, they are difficult to apply to blockchains with large blocks due to generally intractable code guarantees for large codelengths (LDPC), large decoding complexity (2D-RS), or large coding fraud proof sizes (2D-RS). We address these issues by proposing the novel Polar Coded Merkle Tree (PCMT) which is a Merkle Tree built from the encoding graphs of polar codes and a specialized polar code construction called Sampling-Efficient Freezing (SEF). We demonstrate that the PCMT with SEF polar codes performs well in detecting DA attacks for large block sizes.