Safeguarding Blockchain and Dlts From Arbitrary and Malicious Content

Public blockchains and distributed ledger technologies (DLTs) provide reliable distributed, decentralized datasharing, with consensus mechanisms and cryptographic security, data integrity, transparency and trust. Though this transparency and open access allows malicious actors to record arbitrary information to the DLT by exploiting free-form editable text fields in request headers or transaction bodies. The authors propose an architecture that runs external agents interfaced with blockchains, capable of filtering unwanted content to mitigate this threat. Implementation of a resource description framework (RDF) based verification mechanism for blockchain input fields, and an alternate approach using natural language processing (NLP) are then described. Finally, the efficiency and effectiveness of the solution is demonstrated on a blockchain deployment.

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Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/icnp61940.2024.10858544
Citations
2
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
1.56
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article

Safeguarding Blockchain and Dlts From Arbitrary and Malicious Content

Seán Ahearne, Tarek Zaarour, Alan Barnett, Merry Globin et al.
2 citations
Blockchain Technology Applications and Security
1.56
article

Safeguarding Blockchain and Dlts From Arbitrary and Malicious Content

Seán Ahearne, Tarek Zaarour, Alan Barnett, Merry Globin, Khalid Ahmed
article en
2 citations

Abstract

Public blockchains and distributed ledger technologies (DLTs) provide reliable distributed, decentralized datasharing, with consensus mechanisms and cryptographic security, data integrity, transparency and trust. Though this transparency and open access allows malicious actors to record arbitrary information to the DLT by exploiting free-form editable text fields in request headers or transaction bodies. The authors propose an architecture that runs external agents interfaced with blockchains, capable of filtering unwanted content to mitigate this threat. Implementation of a resource description framework (RDF) based verification mechanism for blockchain input fields, and an alternate approach using natural language processing (NLP) are then described. Finally, the efficiency and effectiveness of the solution is demonstrated on a blockchain deployment.

DELL (Ireland) (IE)
Openalex Percentile: Top 11%
Blockchain Technology Applications and Security
1.56
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