The rapid growth of e-commerce has led to an increased prevalence of automated bots engaging in fraudulent activities. Bot is a software application programmed to execute specific tasks to simulate humans in social or web activities. Despite online businesses' continuous efforts to enhance user experience through the adoption of modern technologies, the disruptive presence of malicious bots poses a significant threat to the company's revenue and overall success. As bots constitute up to 70% of traffic on e-commerce platforms like Amazon, this is a critical problem. This thesis will investigate the approaches to mitigate the effect of bot traffic on data centers.

Work Packages

1. Analyze the bot traffic data
2. Extract features
3. Use in-network machine learning method to mitigate the impact

Preferred skills set but not necessary

• Python programming
• ML basics
• Nice to have Linux scripts experience