Neuromorphic Computing for Real-Time Threat Detection in Banking Networks: A Novel Approach

This research work looks into the application of Neuromorphic computing for real-time threat detection in banking networks. The emergence of Neuromorphic computing which is inspired by the human brain’s neural structure and function offers a more sophisticated and promising solution to the challenges of detecting threat, financial crimes and cyber-attacks. The research also identified limitations of the traditional threat detection approaches in the banking networks and then highlighted the benefits with the introduction of Neuromorphic computing in threat detection and prevention. The Author further explored the key challenges faced in implementing Neuromorphic computing and then recommended potential future directions for research and development in the field. The research finally concluded that Neuromorphic computing has the potential to transform threat detection processes in the banking network and improve financial security generally in financial institutions.

Authors

Publication Details

Journal
International Journal of Scientific Research and Modern Technology.
Published
2025-08-27
DOI
https://doi.org/10.38124/ijsrmt.v4i8.714
Citations
1
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Neuromorphic Computing for Real-Time Threat Detection in Banking Networks: A Novel Approach

Giwa Olajumoke Sherifat
1 citations
International Journal of Scientific Research and Modern Technology.
Anomaly Detection Techniques and Applications
2.48
article

Neuromorphic Computing for Real-Time Threat Detection in Banking Networks: A Novel Approach

Giwa Olajumoke Sherifat
article en
1 citations

Abstract

This research work looks into the application of Neuromorphic computing for real-time threat detection in banking networks. The emergence of Neuromorphic computing which is inspired by the human brain’s neural structure and function offers a more sophisticated and promising solution to the challenges of detecting threat, financial crimes and cyber-attacks. The research also identified limitations of the traditional threat detection approaches in the banking networks and then highlighted the benefits with the introduction of Neuromorphic computing in threat detection and prevention. The Author further explored the key challenges faced in implementing Neuromorphic computing and then recommended potential future directions for research and development in the field. The research finally concluded that Neuromorphic computing has the potential to transform threat detection processes in the banking network and improve financial security generally in financial institutions.

International Journal of Scientific Research and Modern Technology.
Openalex Percentile: Top 9%
Anomaly Detection Techniques and Applications
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.