CRLGOct 29, 2018

Characterizing Entities in the Bitcoin Blockchain

arXiv:1810.11956v195 citations
Originality Incremental advance
AI Analysis

This addresses privacy risks for Bitcoin users by revealing vulnerabilities in transaction patterns, though it is incremental as it builds on prior studies of identity leakage.

The paper tackled the problem of privacy leakage in Bitcoin's pseudonymous transactions by analyzing transaction patterns around entities, showing that even a weak attacker can characterize entity properties using newly defined features.

Bitcoin has created a new exchange paradigm within which financial transactions can be trusted without an intermediary. This premise of a free decentralized transactional network however requires, in its current implementation, unrestricted access to the ledger for peer-based transaction verification. A number of studies have shown that, in this pseudonymous context, identities can be leaked based on transaction features or off-network information. In this work, we analyze the information revealed by the pattern of transactions in the neighborhood of a given entity transaction. By definition, these features which pertain to an extended network are not directly controllable by the entity, but might enable leakage of information about transacting entities. We define a number of new features relevant to entity characterization on the Bitcoin Blockchain and study their efficacy in practice. We show that even a weak attacker with shallow data mining knowledge is able to leverage these features to characterize the entity properties.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes