In today's digital landscape, cybersecurity threats are becoming increasingly sophisticated, posing significant challenges to organizations worldwide. Vloe is seeking to enhance its cybersecurity measures by integrating artificial intelligence to detect and mitigate potential threats more effectively. The project aims to develop a prototype AI model that can analyze network traffic data and identify anomalies indicative of cyber threats. Learners will apply their knowledge of machine learning algorithms and cybersecurity principles to create a solution that can adapt to evolving threats. The project will involve researching existing AI models used in cybersecurity, selecting appropriate algorithms, and training the model using sample datasets. The ultimate goal is to provide Vloe with a proof-of-concept tool that demonstrates the potential of AI in strengthening cybersecurity defenses.

The deliverables for this project include a comprehensive report detailing the research findings on AI applications in cybersecurity, a trained AI model capable of detecting network anomalies, and a presentation showcasing the model's functionality and potential impact. Additionally, learners will provide documentation on the model's development process and recommendations for future improvements.