In fields like behavior monitoring, traffic analysis, and anomaly detection, stronger data correlation techniques are required due to the increasing complexity of computer networks. These methods are crucial for getting a comprehensive view of the events produced by an increasing number of network and security devices. Networks and systems must be continuously strengthened and safeguarded, and cybersecurity must be able to provide all-encompassing protection at various infrastructure and technological levels.

AIS foresees advancements in cybersecurity and uses big data analysis, video analysis, forensic, and intelligence approaches applied to cybersecurity to enhance decision-making in order to respond effectively to potential threats: designing the emergency response procedures, making the strategic decisions that will shape medium- to long-term planning, and defining the ideal security infrastructure.

In order to monitor system security and analyze all connected occurrences, AIS employs these methodologies and solutions to combine technical platforms at the service of Security Operation Centres (SOCs). Additionally, they assist Intelligence Operation Centres (IOCs), which disseminate data on new threats, attack techniques, and other events. This enables proactive identification of threats and techniques used to breach systems before they might have more serious repercussions.

In this situation, training is crucial. AIS has integrated virtualization, emulation, and simulation techniques to provide flexible, dynamic environments to replicate large, extensive networks for cybersecurity training. These settings can serve as testing grounds for various goods, programs, and protocols.

In order to respond efficiently even when information is limited, AIS researches and develops Artificial Intelligence (AI) technologies and applications with an emphasis on physical and cybersecurity. It uses High Performance Computing functions and AI applied to cyber threat detection.