Revolutionizing Retail Cybersecurity: Integrating Machine Learning and Blockchain for Secure Transactions

EasyChair Preprint no. 12701

Abstract

In an era where digital transactions reign supreme, the security of retail transactions is of paramount importance. Cybersecurity threats loom large, posing significant risks to both consumers and businesses alike. This paper explores innovative solutions leveraging the synergistic power of machine learning and blockchain technology to fortify retail cybersecurity. Machine learning algorithms offer advanced threat detection capabilities, enabling real-time identification of suspicious activities and potential fraud. Meanwhile, blockchain technology provides a decentralized and immutable ledger system, ensuring the integrity and transparency of transaction records. By integrating these technologies, retail businesses can create a robust ecosystem for secure transactions, fostering trust and confidence among customers while safeguarding sensitive financial data. This paper discusses the principles, benefits, and challenges associated with the integration of machine learning and blockchain in retail cybersecurity, highlighting practical applications and future directions in this evolving landscape.

Keyphrases: Blockchain, Data Integrity, decentralization, financial security, fraud detection, machine learning, Retail Cybersecurity, Secure Transactions, Threat Detection, Trust

@Booklet{EasyChair:12701,
  author = {Jonny Bairstow},
  title = {Revolutionizing Retail Cybersecurity: Integrating Machine Learning and Blockchain for Secure Transactions},
  howpublished = {EasyChair Preprint no. 12701},

  year = {EasyChair, 2024}}