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Erasing Data from Blockchain Nodes
Erasing Data from Blockchain Nodes
It is a common narrative that blockchains are immutable and so it is technically impossible to erase data stored on them. For legal and ethical reasons, however, individuals and organizations might be compelled to erase locally stored data, be it encoded on a blockchain or not. The common assumption for blockchain networks like Bitcoin is that forcing nodes to erase data contained on the blockchain is equal to permanently restricting them from participating in the system in a full-node role. Challenging this belief, in this paper, we propose and demonstrate a pragmatic approach towards functionality-preserving local erasure (FPLE). FPLE enables full nodes to erase infringing or undesirable data while continuing to store and validate most of the blockchain. We describe a general FPLE approach for UTXO-based (i.e., Bitcoin-like) cryptocurrencies and present a lightweight proof-of-concept tool for safely erasing transaction data from the local storage of Bitcoin Core nodes. Erasing nodes continue to operate in tune with the network even when erased transaction outputs become relevant for validating subsequent blocks. Using only our basic proof-of-concept implementation, we are already able to safely comply with a significantly larger range of erasure requests than, to the best of our knowledge, any other full node operator so far.
Accepted at IEEE Security & Privacy on the Blockchain (IEEE S&B) 2019; https://blockchain.kcl.ac.uk/ieee-sb2019/
- Weizenbaum Institut Germany
- Humboldt-Universität zu Berlin Germany
FOS: Computer and information sciences, Computer Science - Computers and Society, Computer Science - Cryptography and Security, Computers and Society (cs.CY), Cryptography and Security (cs.CR)
FOS: Computer and information sciences, Computer Science - Computers and Society, Computer Science - Cryptography and Security, Computers and Society (cs.CY), Cryptography and Security (cs.CR)
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citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).47 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
