Blockchain technology provides trust and transparency without the need for intermediaries, serving as a secure solution for recording diverse information in many fields of application. Blockchains can also run decentralized applications (DApps), but their ever-growing popularity has led to a surge in the amount of information recorded on-chain. This has also made resource-constrained light nodes more dependent on untrusted full nodes for fetching such data. As a result, the need for developing efficient techniques to retrieve blockchain data, as well as query authentication protocols ensuring result integrity, has become increasingly pressing. On-chain data also offer interesting insights on user interactions in public blockchain systems. Indeed, their analysis allows for understanding patterns, discovering user communities, detecting anomalies, and ensuring network security. In this thesis we present our twofold contribution to the field, structured in two distinct, yet complementary, lines of research. First, we study query authentication techniques to enable efficient and authenticated retrieval of blockchain data. Specifically, we propose protocols and authenticated data structures that ensure the correctness of information returned by full nodes to light nodes whenever the latter seek access to on-chain data. We present algorithms for constructing, querying, and verifying results using our authenticated data structures, detailing also their computational complexity. Finally, we evaluate our proposals through experimental analyses to assess their performance in realistic scenarios. To this aim, we utilize real data sets comprising geospatial data and Ethereum event data as reference use cases. The second line of research presented in this thesis concerns the analysis of transaction data from Bitcoin and Ethereum, the most popular public blockchains. Concerning the former, we conduct a rich set of analyses of dust transactions, which include very small amounts of currency and are typically issued to achieve unconventional side effects rather than exchanging value. We identify the main dust creators and consumers, discuss how consumption has evolved over time, and finally study the impact of these transactions on the security of the Bitcoin network. As for Ethereum, we focus on fungible tokens, namely interchangeable and transferable assets utilized by DApps. We study the topological properties of networks modeling token exchanges and investigate their possible relations with the token semantics.

Query Authentication Protocols and Data Analysis on Blockchain Systems

LOPORCHIO, MATTEO
2024

Abstract

Blockchain technology provides trust and transparency without the need for intermediaries, serving as a secure solution for recording diverse information in many fields of application. Blockchains can also run decentralized applications (DApps), but their ever-growing popularity has led to a surge in the amount of information recorded on-chain. This has also made resource-constrained light nodes more dependent on untrusted full nodes for fetching such data. As a result, the need for developing efficient techniques to retrieve blockchain data, as well as query authentication protocols ensuring result integrity, has become increasingly pressing. On-chain data also offer interesting insights on user interactions in public blockchain systems. Indeed, their analysis allows for understanding patterns, discovering user communities, detecting anomalies, and ensuring network security. In this thesis we present our twofold contribution to the field, structured in two distinct, yet complementary, lines of research. First, we study query authentication techniques to enable efficient and authenticated retrieval of blockchain data. Specifically, we propose protocols and authenticated data structures that ensure the correctness of information returned by full nodes to light nodes whenever the latter seek access to on-chain data. We present algorithms for constructing, querying, and verifying results using our authenticated data structures, detailing also their computational complexity. Finally, we evaluate our proposals through experimental analyses to assess their performance in realistic scenarios. To this aim, we utilize real data sets comprising geospatial data and Ethereum event data as reference use cases. The second line of research presented in this thesis concerns the analysis of transaction data from Bitcoin and Ethereum, the most popular public blockchains. Concerning the former, we conduct a rich set of analyses of dust transactions, which include very small amounts of currency and are typically issued to achieve unconventional side effects rather than exchanging value. We identify the main dust creators and consumers, discuss how consumption has evolved over time, and finally study the impact of these transactions on the security of the Bitcoin network. As for Ethereum, we focus on fungible tokens, namely interchangeable and transferable assets utilized by DApps. We study the topological properties of networks modeling token exchanges and investigate their possible relations with the token semantics.
4-mag-2024
Italiano
authenticated data structure
Bitcoin
blockchain
cryptocurrency
data analysis
Ethereum
Bernasconi, Anna
Di Francesco Maesa, Damiano
Ricci, Laura Emilia Maria
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/216202
Il codice NBN di questa tesi è URN:NBN:IT:UNIPI-216202