Off-chain Protocols for Blockchain: Methodologies and Applications

Blockchain technology establishes a foundation of integrity and transparency across de- centralized networks of mutually distrusting nodes, offering a trust-minimized security layer for a wide range of applications. However, while the introduction of these systems revolutionized distributed computing, their widespread adoption has exposed critical limitations that hinder their utility for general-purpose computation at scale. Among these challenges are the restricted expressivity of the most widely adopted blockchain protocols and the inherent scalability bottlenecks that constrain throughput significantly and achieve worse results in comparison with centralized alternatives. The off-chain paradigm emerges as a promising design strategy to mitigate these issues. This approach shifts the burden of computation or data management external to the primary system, utilizing cryptographic or economic mechanisms to enforce the validity of these external operations on the blockchain only when necessary. In this the- sis, we advance the state of the art by introducing novel off-chain protocols designed to address the expressivity and scalability constraints of distinct blockchain architectures. We demonstrate the practicality of these contributions by devising concrete applications that leverage them as fundamental building blocks, enabling functionalities that were previously infeasible or that significantly reduce reliance on trusted intermediaries. First, we focus on Bitcoin, the most prominent blockchain system. We introduce off-chain protocols that enable practical, arbitrary computation on Bitcoin without re- quiring modifications to its consensus rules or execution model. We illustrate how these primitives allow for the construction of applications, such as trust-minimized bridges, that operate with significantly weaker trust assumptions than the current state of the art. Then, we investigate high-throughput architectures. Using Algorand as a reference, we demonstrate that off-chain protocols can further enhance performance metrics (latency and cost) even for blockchain systems that are already optimized for scalability. Fi- nally, we explore the impact of off-chain protocols in industrial contexts. We propose a framework based on the HybridDLT system to enable the execution of computationally intensive tasks (specifically Machine Learning pipelines) within an environment that inherits the strict auditability and integrity guarantees of the blockchain.