Safeguarding seniors: How Network Security and AI Prevent Elder Fraud
Sanchayan Chakraborty
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 2, 576-586
Abstract:
This article explores the critical role of advanced network security and artificial intelligence in protecting elderly populations from financial fraud and exploitation. As cybercriminals increasingly target vulnerable seniors, sophisticated technological countermeasures have emerged to create multi-layered defense systems. The article examines six key protective approaches: advanced threat detection systems that identify unusual patterns in financial transactions; behavioral analysis and anomaly detection that establish personalized usage baselines; enhanced authentication methods designed specifically for elderly users' unique needs; scam call and message filtering that operates at the telecommunications infrastructure level; predictive fraud prevention that anticipates emerging scam vectors before widespread impact; and collaborative protection networks that share intelligence across institutions. Through detailed case studies and technical analysis, the article demonstrates how these interconnected systems can effectively identify and neutralize fraudulent activities before seniors experience significant harm. The findings suggest that comprehensive digital protection frameworks can dramatically reduce elder fraud while preserving autonomy, highlighting the importance of age-inclusive design principles in cybersecurity solutions aimed at vulnerable populations.
Keywords: Behavioral Analysis; Elder Fraud Prevention; AI-Driven Security; Collaborative Protection Networks; Biometric Authentication (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112397
References: Add references at CitEc
Citations:
Downloads: (external link)
https://ijsrcseit.com/home/article/view/CSEIT25112397 Article URL (text/html)
https://ijsrcseit.com/home/article/download/CSEIT25112397/CSEIT25112397 Full text (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i2:id:1127
DOI: 10.32628/CSEIT25112397
Access Statistics for this article
More articles in International Journal of Scientific Research in Computer Science, Engineering and Information Technology from International Journal of Scientific Research in Computer Science, Engineering and Information Technology
Bibliographic data for series maintained by Pankaj Sharma (USA) ().