Enhancing Cybersecurity in Banking Through AI and SVM Algorithms

Banking industry is becoming an increasingly rewarding target for cybercriminals because of the large amount of sensitive monetary data and money saved inside banking systems. As a result, enhancing cyber security measures has become a vital priority for banks to shield their systems and patron records. To fight the ever-evolving threat panorama, banks are currently turning to synthetic intelligence (AI) and aid vector machine (SVM) algorithms. Those advanced technologies can significantly improve cyber security in banking by identifying and preventing cyber assaults before they can cause major damage. AI technology can examine considerable quantities of facts in real-time, allowing banks to locate anomalies or suspicious behavior that could indicate a cyber assault. SVM algorithms, on the other hand, can efficaciously categorize and classify exclusive kinds of cyber threats, enabling banks to prioritize and respond to cyber assaults more effectively. Using AI and SVM algorithms can also help banks detect and mitigate internal threats, such as worker fraud or data breaches.

Authors

Institutions

Publication Details

Published
2025-05-29
DOI
https://doi.org/10.1109/netcrypt65877.2025.11102619
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Cybersecurity in Banking Through AI and SVM Algorithms

Rishabh Bhardwaj, Manas Kumar Nanda, K Preetham, Ashu Katyal et al.
Blockchain Technology Applications and Security
article

Enhancing Cybersecurity in Banking Through AI and SVM Algorithms

Rishabh Bhardwaj, Manas Kumar Nanda, K Preetham, Ashu Katyal, Shweta Singh, Murugan
article en

Abstract

Banking industry is becoming an increasingly rewarding target for cybercriminals because of the large amount of sensitive monetary data and money saved inside banking systems. As a result, enhancing cyber security measures has become a vital priority for banks to shield their systems and patron records. To fight the ever-evolving threat panorama, banks are currently turning to synthetic intelligence (AI) and aid vector machine (SVM) algorithms. Those advanced technologies can significantly improve cyber security in banking by identifying and preventing cyber assaults before they can cause major damage. AI technology can examine considerable quantities of facts in real-time, allowing banks to locate anomalies or suspicious behavior that could indicate a cyber assault. SVM algorithms, on the other hand, can efficaciously categorize and classify exclusive kinds of cyber threats, enabling banks to prioritize and respond to cyber assaults more effectively. Using AI and SVM algorithms can also help banks detect and mitigate internal threats, such as worker fraud or data breaches.

Jain University (IN), Siksha O Anusandhan University (IN), Maharishi University of Management and Technology (IN), Sathyabama Institute of Science and Technology (IN), Chitkara University (IN)
Decent work and economic growth
Openalex Percentile: Top 69%
Blockchain Technology Applications and Security
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.