TY - GEN
T1 - Strategic Safeguards
T2 - 4th International Conference on Computing and Communication Networks, ICCCN 2024
AU - Mohata, Rishabh
AU - Chandrakar, Akash
AU - Yang, Tiansheng
AU - Rathore, Rajkumar Singh
AU - Raj, Aaryan
AU - Tripathy, Hrudaya Kumar
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025/7/3
Y1 - 2025/7/3
N2 - The issuance of phony currency adversely affects authentic money leading to fluctuations in the market, interruptions in commerce, and inflation. Public confidence in financial systems is jeopardized by this. Our research presents a sophisticated authentication model that integrates Recurrent Neural Networks (RNNs) with Multi-head Attention in order to fight large-scale forgery. This technique uses neural network learning and focus pattern recognition to effectively differentiate between authentic and phony cash. In challenging economic circumstances, it offers a complete solution for reliable phony cash identification, boosting security. It is shown that the RNN Multi-head model is a useful instrument for reinforcing monetary systems and promoting general economic stability.
AB - The issuance of phony currency adversely affects authentic money leading to fluctuations in the market, interruptions in commerce, and inflation. Public confidence in financial systems is jeopardized by this. Our research presents a sophisticated authentication model that integrates Recurrent Neural Networks (RNNs) with Multi-head Attention in order to fight large-scale forgery. This technique uses neural network learning and focus pattern recognition to effectively differentiate between authentic and phony cash. In challenging economic circumstances, it offers a complete solution for reliable phony cash identification, boosting security. It is shown that the RNN Multi-head model is a useful instrument for reinforcing monetary systems and promoting general economic stability.
KW - Authentic money
KW - Multi-head Attention
KW - Phony currency
KW - Recurrent Neural Networks
UR - https://www.scopus.com/pages/publications/105010593273
U2 - 10.1007/978-981-96-3250-3_22
DO - 10.1007/978-981-96-3250-3_22
M3 - Conference contribution
AN - SCOPUS:105010593273
SN - 9789819632497
T3 - Lecture Notes in Networks and Systems
SP - 273
EP - 284
BT - Proceedings of 4th International Conference on Computing and Communication Networks, ICCCN 2024
A2 - Kumar, Akshi
A2 - Swaroop, Abhishek
A2 - Shukla, Pancham
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 17 October 2024 through 18 October 2024
ER -