Can we use ML tasks as a proof of work in consensus algorithm

Blockchains such as Bitcoin and Ethereum currently are computational wasteful. On an annual basis both blockchains consume over a 70 terawatt-hours (TWh) of energy on computational resources to secure the network, which is similar to the annual energy consumption of Switzerland. These computational resources are used to reverse a cryptographic hash function (which is called a consensus algorithm) that is a solution to a puzzle, but serves no other purpose. Such amount of computational resources should be used more efficiently. Our aim is to use the large amount of computational resources more efficient by replacing the cryptographic hash function with a machine learning task. We focus on the Ethereum network as its computational power is not limited to solving hash functions only, as is mostly the case in Bitcoin. However, our intended solution can be generalized to any blockchain that is currently a computational wasteful.

Output

Publication: Review paper

Project Partners:

• ING Groep NV, Dilhan Thilakarathne

Primary Contact: Dilhan Thilakarathne, ING