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
- Rishabh Bhardwaj (ORCID: https://orcid.org/0000-0003-1561-4286)
- Manas Kumar Nanda
- K Preetham
- Ashu Katyal (ORCID: https://orcid.org/0009-0005-7377-6891)
- Shweta Singh (ORCID: https://orcid.org/0000-0002-1561-2494)
- Murugan
Institutions
- 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)
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