Research for NFT and Smart Contract in Ethereum & Algorand
In recent months, we have heard a lot of talk in the news and media about digital artworks, referring to them as NFT, selling for millions. For example, Christie's auction house sold a digital painting for $69 million [10]. The NBA (National Basketball Association) through the NBA top shop service sells basketball movies for over 250 million dollars [15]. These just mentioned are just some of the examples related to NFT commercialization. The term NFT refers to an acronym of the English word Non Fungible Token; NFTs can be thought of as certificates that attest to the authenticity, uniqueness and ownership of a digital file. These properties are guaranteed through the use of the blockchain. NFTs are considered by some to be the right and long-awaited way to give value and uniqueness to digital content that would otherwise struggle to find it. The opposite is the opinion of those who consider them little more than a speculative bubble. Ethereum's blockchain is currently the most widely used network for the creation and distribution of NFTs. However, the high transaction costs and scalability issues of the Ethereum network may be a barrier to entry for mass deployment of this particular type of product. However, there are some blockchains that aim to eliminate these problems. One of these is Algorand which aims to be secure, scalable, and decentralized. The goal of this thesis is to analyze the standards used on the Ethereum network (ERC-721) for the creation of NFTs (Chapter 2), explaining their structure, characteristics, and related issues and analyze the possibility of replicating them on the Algorand network. We will then move on to the analysis of smart contracts (Chapter 3) that enable the creation and exchange of NFTs. We will also analyze how to combine the various Algorand technologies to create something unique (Chapter 5). Finally, we will come to the design part where we will present a custom logic that allows the management and exchange of NFTs with other users in the network (Chapter 6). Finally, the conclusions will show the results achieved in this thesis.
