Publication2021
Developing Customized and Secure Blockchains with Deep Federation Learning to Prevent Successive Attacks
- Peace, Justice and Strong Institutions
- Partnerships for the Goals
- Good Governance and Security
The record
- Type
- Publication
- Date
- 1 January 2021
- Level
- International — held abroad
- Journal
- Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics
- Volume
- 12605 LNCS
- Pages
- 31-43
- Published
- 1 January 2021
- DOI
- 10.1007/978-3-030-67550-9_3
- Scopus ID
- 85101374593
- ISSN
- 03029743
- Authors
- 3
- Open access
- No
- Citations
- 0
- International co-authorship
- Yes
- Co-author countries
- FR, IE, IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
16.4 Significantly reduce illicit financial and arms flows and combat all forms of organized crime
Federated learning with LSTM autoencoders for detecting anomalous blockchain transactions, enhancing distributed system security against successive cyberattacks
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-4 Good Governance and Security
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 16 label. Federated learning with LSTM autoencoders for detecting anomalous blockchain transactions, enhancing distributed system security against successive cyberattacks
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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Citing this record
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KIIT Deemed to be University. “Developing Customized and Secure Blockchains with Deep Federation Learning to Prevent Successive Attacks”. Kortex.