TL;DR: A proposed cryptocurrency-payment system using blind signatures and a proxy node, with RNN, GNN, and reinforcement-learning components layered on top.
About This Document
The paper targets public-ledger privacy exposure and confirmation delay. Its proxy handles transaction requests through a blind-signature protocol, while the proposed learning components predict confirmation outcomes, detect scams, and adjust proxy behavior.
Why Bitcoin People May Care
This is a proposed model, not proof of a production-ready payment network. It is useful because it puts several current research habits in one place: privacy through blind signatures, faster settlement through an intermediary layer, and machine learning assigned to fraud and routing decisions.
Document Details
• Title: A Deep Learning-Integrated Proxy Model for Efficient Cryptocurrency Payments
• Author / organization: Vinay Kumar Kasula, Akhila Reddy Yadulla, Bhargavi Konda, Mounica Yenugula, Supraja Ayyamgari
• Year: 2025
• Document type: Research paper
• Pages: 17
Download access
Unlock a direct PDF download of this document. The download is hosted externally. CacheRat provides researched identification and access; purchase does not transfer ownership or expand the document’s existing usage rights.
#pdf #cryptocurrency #payments #deep_learning
About This Document
The paper targets public-ledger privacy exposure and confirmation delay. Its proxy handles transaction requests through a blind-signature protocol, while the proposed learning components predict confirmation outcomes, detect scams, and adjust proxy behavior.
Why Bitcoin People May Care
This is a proposed model, not proof of a production-ready payment network. It is useful because it puts several current research habits in one place: privacy through blind signatures, faster settlement through an intermediary layer, and machine learning assigned to fraud and routing decisions.
Document Details
• Title: A Deep Learning-Integrated Proxy Model for Efficient Cryptocurrency Payments
• Author / organization: Vinay Kumar Kasula, Akhila Reddy Yadulla, Bhargavi Konda, Mounica Yenugula, Supraja Ayyamgari
• Year: 2025
• Document type: Research paper
• Pages: 17
Download access
Unlock a direct PDF download of this document. The download is hosted externally. CacheRat provides researched identification and access; purchase does not transfer ownership or expand the document’s existing usage rights.
#pdf #cryptocurrency #payments #deep_learning
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