This training introduces honeypots — deliberately exposed, closely monitored decoy systems used to detect, divert and study attackers. Starting from first principles, it explains how deception turns almost any interaction with a decoy into a high-confidence security signal, and where honeypots fit alongside firewalls, IDS/IPS and antivirus rather than replacing them.
Across the module you'll explore the main types of honeypot (by interaction level and by purpose), common categories and tools such as Cowrie, Dionaea, Conpot, T-Pot and canary tokens, as well as honeynets and honeytokens. You'll learn how to deploy decoys safely with proper isolation, logging and SIEM integration, how attackers try to fingerprint and evade honeypots, and the benefits and limitations of the approach. The training also covers the legal and ethical considerations — including GDPR and the rule against "hacking back" — and practical, low-cost ways for smaller organisations to get started.
By the end, you'll be able to explain what honeypots are, choose the right type for a given goal, identify suitable tooling, plan a safe deployment, and recognise the key operational and legal constraints.
This course introduces the principles and operation of Network Intrusion Detection Systems (NIDS), focusing on how they monitor, analyze, and detect malicious activities within network traffic. Students will explore key detection techniques, including rule-based, anomaly-based, and hybrid methods, and learn to identify common attacks such as DoS, port scanning, and SQL injection. The course also covers sensor deployment, alert interpretation, and the roles of NIDS operators and managers in maintaining network security. Emphasis is placed on understanding system advantages, limitations, and practical applications in securing modern networks against both known and zero-day threats.
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