Secure Retail: Harnessing Machine Learning, Business Analytics, and Blockchain for Cybersecurity Excellence

EasyChair Preprint 12695

Abstract

In today's retail landscape, cybersecurity is a paramount concern amidst the rapid digitization of operations and the ever-present threat of cyber-attacks. This paper explores the integration of machine learning, business analytics, and blockchain applications as essential components of a comprehensive cybersecurity strategy tailored specifically for the retail industry. By harnessing the power of these advanced technologies, retailers can effectively mitigate risks, protect customer data, and ensure the integrity of transactions. Machine learning plays a pivotal role in threat detection, enabling retailers to identify and respond to malicious activities in real-time. Business analytics further enhances security measures by providing predictive insights into potential vulnerabilities and enabling proactive risk management strategies. Additionally, blockchain technology offers a secure and immutable ledger for transactional data, safeguarding against tampering and ensuring transparency and accountability throughout the supply chain. Through a combination of theoretical frameworks and practical case studies, this paper demonstrates the tangible benefits of leveraging machine learning, business analytics, and blockchain in retail cybersecurity. By adopting a data-driven approach to security, retailers can stay ahead of evolving threats and foster a culture of trust and confidence among their customers.

Keyphrases: Blockchain, Business Analytics, Retail Cybersecurity, Threat Detection, Transaction Integrity, machine learning, risk management

@booklet{EasyChair:12695,
  author    = {Deep Himmatbhai Ajabani},
  title     = {Secure Retail: Harnessing Machine Learning, Business Analytics, and Blockchain for Cybersecurity Excellence},
  howpublished = {EasyChair Preprint 12695},
  year      = {EasyChair, 2024}}