The goal of the SENTAI project is to enhance cybersecurity solutions by developing a comprehensive artificial intelligence-based system that addresses the identified research gaps. To overcome the lack of comprehensive analysis using multiple data sources, the project will implement an integrated approach, considering diverse datasets to improve the overall understanding of AI performance across various scenarios and data types.

Additionally, to tackle the challenge of training and testing AI models on outdated data, the project will focus on incorporating contemporary datasets, ensuring that the system’s training reflects current security landscapes. Emphasizing a broader perspective, the project aims to design AI-based cybersecurity solution that integrate seamlessly into the entire system, promoting relevance to realworld scenarios.

Furthermore, the project will prioritize the evaluation against real-world scenarios to ensure the practical applicability of the developed solutions. By adopting a holistic approach that considers a broader range of attack types and scenarios, the system will be designed to effectively address diverse cybersecurity challenges.

Lastly, in addressing the big-data problem, the project will focus on developing robust infrastructure and methodologies for the storage and analysis of extensive security data. Effectively managing and extracting meaningful insights from this vast dataset will be a key component of the project’s efforts, enabling timely threat identification and mitigation.