Shielding Financial Data: Next-Gen Security Measures in Edge Computing

EasyChair Preprint 14437

Abstract

The proliferation of edge computing in financial services has introduced a transformative approach to data processing, offering reduced latency and enhanced operational efficiency. However, this paradigm shift also brings forth significant security challenges, necessitating robust and innovative measures to safeguard sensitive financial data. This paper delves into the next-generation security strategies essential for protecting financial information at the edge. We explore the current landscape of edge computing in the financial sector, identifying key vulnerabilities and potential attack vectors. A comprehensive analysis of advanced encryption techniques, secure data transmission protocols, and edge-specific threat detection mechanisms is presented. Additionally, we examine the integration of artificial intelligence and machine learning to enhance real-time security monitoring and anomaly detection. By assessing case studies and real-world applications, the paper underscores the critical importance of adopting cutting-edge security measures to mitigate risks and ensure regulatory compliance. Ultimately, this research aims to provide a roadmap for financial institutions to fortify their edge computing infrastructure, thereby ensuring the integrity, confidentiality, and availability of financial data in an increasingly distributed computing environment.

Keyphrases: Artificial Intelligence, Financial, computing

@booklet{EasyChair:14437,
  author    = {Adeoye Ibrahim},
  title     = {Shielding Financial Data: Next-Gen Security Measures in Edge Computing},
  howpublished = {EasyChair Preprint 14437},
  year      = {EasyChair, 2024}}