EFFECTIVE ANALYSIS OF CYBER-ATTACK PREVENTION USING MACHINE LEARNING TECHNIQUES IN RETAILING
Abstract - The development of the internet has transformed the way of traditional shopping into online and has established a need for protection of online retailing due to incessant malicious cyber-attacks. This study investigates cyber-attack prevention practices of online retailing in the context of the developing world. It explores the foundation for advanced machine-learning research in protecting online retailers and how it will effectively designa framework for developing countries. The qualitative case study design with a semi-structured data collection mechanism, i.e., face-to-face interviews and company documents, can be used. Various data collection procedures using purposive sampling are emphasized, like interviews with authorized cyber security officials within the online retail sector of the majority world. The study will empirically investigate the effects of machine-learning-based techniques for cyber-attack prevention in an online retail setting.
Keywords - Cyber-Attacks, Cyber-Threats, Retailers, Machine-Learning, Cyber-Attack Prevention