Cyber ​​incidents and strategies for their prevention

The use of advanced data‑protection technologies such as encryption, intrusion detection systems (IDS), artificial intelligence (AI), and machine learning (ML) has become essential for effective defense against sophisticated cyber threats.

• Encryption ensures that data remains unreadable to unauthorised individuals, even if it falls into their hands. Examples include emerging solutions such as post‑quantum cryptography and quantum key–based protection (e.g., Quantinuum).
• Intrusion Detection Systems (IDS) monitor network traffic or device activity (NIDS and HIDS), searching for known attack patterns or anomalies. Modern IDS platforms use both signature‑based and anomaly‑based detection, often supported by machine learning to identify unexpected threats.
• Artificial intelligence and machine learning enable automated analysis of large volumes of security data, rapid threat detection, and proactive defense. These solutions rely on models that identify anomalies in network traffic, malicious software, and user behaviour, and automatically generate alerts.
• AI also optimises encryption by automating key management and identifying weaknesses in encryption algorithms, for example, in the context of post‑quantum encryption and improving the efficiency of cryptographic systems.