Formal Methods for Secure Bitcoin Smart Contracts

The notion of smart contracts was introduced in 1997 by Nick Szabo, to describe agreements among mutually distrusting parties that can be automatically enforced without resorting to a trusted intermediary. Then, the idea was mostly forgotten due to the technical impossibility to implement it. The advent of distributed ledger technologies, pioneered by Bitcoin, provided a technical foundation to reshape and develop smart contracts. Since smart contracts handle the ownership of valuable assets, attackers may be tempted to exploit vulnerabilities in their implementation to steal or tamper with these assets. For instance, a series of vulnerabilities in Ethereum contracts have been exploited, causing money losses in the order of hundreds of millions of dollars. Over the last years, a variety of smart contracts for Bitcoin have been proposed, both by the academic community and by that of developers. However, the heterogeneity in their treatment, the informal (often incomplete or imprecise) descriptions, and the use of poorly documented Bitcoin features, poses obstacles to the development of secure smart contracts. Using formal models and domain-specific languages to describe the behaviour of the underlying platform, and to model contracts, could help to overcome these security issues, by reducing the distance between the intended behaviour of a contract and the implementation. In this thesis, we propose a formal model of Bitcoin transactions, which is the foundation for a new process algebra for defining Bitcoin smart contracts. Furthermore, we present a toolchain for developing smart contracts in BitML, a domain-specific language based on the contributions of this thesis. Moreover, we propose a new extension to Bitcoin, called neighbourhood covenants, which extends its expressiveness as a smart contract platform. We then exploit neighbourhood covenants to implement fungible tokens on Bitcoin

The Transaction Graph for Modeling Blockchain Semantics

The advent of Bitcoin paved the way for a plethora of blockchain systems supporting diverse applications beyond cryptocurrencies. Although in-depth studies of the protocols, security, and privacy of blockchains are available, there is no formal model of the transaction semantics that a blockchain is supposed to guarantee. In this work, we fill this gap, motivated by the observation that the semantics of transactions in blockchain systems can be captured by a directed acyclic graph. Such a transaction graph, or TDAG, generally consists of the states and the transactions as transitions between the states, together with conditions for the consistency and validity of transactions. We instantiate the TDAG model for three prominent blockchain systems: Bitcoin, Ethereum, and Hyperledger Fabric. We specify the states and transactions as well as the validity conditions of the TDAG for each one. This demonstrates the applicability of the model and formalizes the transaction-level semantics that these systems aim for

Predictive Modeling for Fair and Efficient Transaction Inclusion in Proof-of-Work Blockchain Systems

This dissertation investigates the strategic integration of Proof-of-Work(PoW)-based blockchains and ML models to improve transaction inclusion, and consequently molding transaction fees, for clients using cryptocurrencies such as Bitcoin. The research begins with an in-depth exploration of the Bitcoin fee market, focusing on the interdependence between users and miners, and the emergence of a fee market in PoW-based blockchains. Our observations are used to formalize a transaction inclusion pattern. To support our research, we developed the Blockchain Analytics System (BAS) to acquire, store, and pre-process a local dataset of the Bitcoin blockchain. BAS employs various methods for data acquisition, including web scraping, web browser APIs, and direct access to the blockchain using Bitcoin Core software. We utilize time-series data analysis as a tool for predicting future trends, and transactions are sampled on a monthly basis with a fixed interval, incorporating a notion of relative time represented by block-creation epochs. We create a comprehensive model for transaction inclusion in a PoW-based blockchain system, with a focus on factors of revenue and fairness. Revenue serves as an incentive for miners to participate in the network and validate transactions, while fairness ensures equal opportunity for all users to have their transactions included upon paying an adequate fee value. The ML architecture used for prediction consists of three critical stages: the ingestion engine, the pre-processing stage, and the ML model. The ingestion engine processes and transforms raw data obtained from the blockchain, while the pre-processing phase transforms the data further into a suitable form for analysis, including feature extraction and additional data processing to generate a complete dataset. Our ML model showcases its effectiveness in predicting transaction inclusion, with an accuracy of more than 90%. Such a model enables users to save at least 10% on transaction fees while maintaining a likelihood of inclusion above 80%. Furthermore, adopting such model based on fairness and revenue, demonstrates that miners' average loss is never higher than 1.3%. Our research proves the efficacy of a formal transaction inclusion model and ML prototype in predicting transaction inclusion. The insights gained from our study shed light on the underlying mechanisms governing miners' decisions, improving the overall user experience, and enhancing the trust and reliability of cryptocurrencies. Consequently, this enables Bitcoin users to better select suitable fees and predict transaction inclusion with notable precision, contributing to the continued growth and adoption of cryptocurrencies

Philosophy of Blockchain Technology - Ontologies

About the necessity and usefulness of developing a philosophy specific to the blockchain technology, emphasizing on the ontological aspects. After an Introduction that highlights the main philosophical directions for this emerging technology, in Blockchain Technology I explain the way the blockchain works, discussing ontological development directions of this technology in Designing and Modeling. The next section is dedicated to the main application of blockchain technology, Bitcoin, with the social implications of this cryptocurrency. There follows a section of Philosophy in which I identify the blockchain technology with the concept of heterotopia developed by Michel Foucault and I interpret it in the light of the notational technology developed by Nelson Goodman as a notational system. In the Ontology section, I present two developmental paths that I consider important: Narrative Ontology, based on the idea of order and structure of history transmitted through Paul Ricoeur's narrative history, and the Enterprise Ontology system based on concepts and models of an enterprise, specific to the semantic web, and which I consider to be the most well developed and which will probably become the formal ontological system, at least in terms of the economic and legal aspects of blockchain technology. In Conclusions I am talking about the future directions of developing the blockchain technology philosophy in general as an explanatory and robust theory from a phenomenologically consistent point of view, which allows testability and ontologies in particular, arguing for the need of a global adoption of an ontological system for develop cross-cutting solutions and to make this technology profitable. CONTENTS: Abstract Introducere Tehnologia blockchain - Proiectare - Modele Bitcoin Filosofia Ontologii - Ontologii narative - Ontologii de intreprindere Concluzii Note Bibliografie DOI: 10.13140/RG.2.2.24510.3360

Modeling Bitcoin Contracts by Timed Automata

Bitcoin is a peer-to-peer cryptographic currency system. Since its introduction in 2008, Bitcoin has gained noticeable popularity, mostly due to its following properties: (1) the transaction fees are very low, and (2) it is not controlled by any central authority, which in particular means that nobody can "print" the money to generate inflation. Moreover, the transaction syntax allows to create the so-called contracts, where a number of mutually-distrusting parties engage in a protocol to jointly perform some financial task, and the fairness of this process is guaranteed by the properties of Bitcoin. Although the Bitcoin contracts have several potential applications in the digital economy, so far they have not been widely used in real life. This is partly due to the fact that they are cumbersome to create and analyze, and hence risky to use. In this paper we propose to remedy this problem by using the methods originally developed for the computer-aided analysis for hardware and software systems, in particular those based on the timed automata. More concretely, we propose a framework for modeling the Bitcoin contracts using the timed automata in the UPPAAL model checker. Our method is general and can be used to model several contracts. As a proof-of-concept we use this framework to model some of the Bitcoin contracts from our recent previous work. We then automatically verify their security in UPPAAL, finding (and correcting) some subtle errors that were difficult to spot by the manual analysis. We hope that our work can draw the attention of the researchers working on formal modeling to the problem of the Bitcoin contract verification, and spark off more research on this topic