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Fortifying Retail Security: Leveraging Business Analytics, Machine Learning, and Blockchain Integration for Enhanced Cyber Protection

EasyChair Preprint 12698

10 pagesDate: March 22, 2024

Abstract

In the era of digital transformation, retail businesses face increasing cybersecurity threats that demand innovative solutions for protection. This paper explores the convergence of business analytics, machine learning, and blockchain technology to fortify retail security. By leveraging advanced analytics, predictive modeling, and anomaly detection, businesses can proactively identify and mitigate potential threats. Machine learning algorithms enhance security measures by continuously learning from data patterns to detect and respond to emerging cyber threats in real-time. Additionally, integrating blockchain technology provides immutable and transparent transaction records, reducing the risk of data tampering and ensuring data integrity throughout the retail supply chain. This paper examines the synergistic potential of these technologies in bolstering retail cybersecurity and proposes strategies for their effective implementation.

Keyphrases: Blockchain Technology, Business Analytics, Data Integrity, Retail Cybersecurity, Supply Chain Security, anomaly detection, machine learning, predictive modeling

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:12698,
  author    = {William Jack},
  title     = {Fortifying Retail Security: Leveraging Business Analytics, Machine Learning, and Blockchain Integration for Enhanced Cyber Protection},
  howpublished = {EasyChair Preprint 12698},
  year      = {EasyChair, 2024}}
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