Artificial Intelligence for Cybersecurity

Code 931II
Credits 6

Learning outcomes

The course aims to introduce the main methods and techniques of artificial intelligence used in information security applications. In particular, the course introduces topics such as data pre-processing, frequent pattern mining and association rules, classification, clustering, anomaly detection. In addition, the course discusses the main attacks against artificial intelligence systems, such as the adversarial classifier evasion and data poisoning, and the related defensive techniques. Finally, the course deals with the main uses of artificial intelligence in information security problems such as the detection of spam/phishing, the detection of intrusions and malware, the detection of online frauds, the analysis of the cyber threat intelligence.
Details of the topics covered:
- Data preprocessing
- Frequent pattern mining
- Classification
- Clustering
- Outlier detection
- Adversarial machine learning
- AI applications for spam and phishing detection
- AI applications for intrusion and malware detection
- AI applications for fraud detection
- Cyber threat intelligence analysis