A cybersecurity application of data science: intrusion detection systems and data poisoning
Rosatelli, Davide (A.A. 2022/2023) A cybersecurity application of data science: intrusion detection systems and data poisoning. Tesi di Laurea in Data science in action, Luiss Guido Carli, relatore Alessio Martino, pp. 73. [Master's Degree Thesis]
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Abstract/Index
Literature review. Intrusion detection systems. Data poisoning. Research questions. Methods. Dataset description and preprocessing. Machine learning models and neural networks. Evaluation techniques. Poisoning techniques. Results. Preventive measures.
References
Bibliografia: pp. 69-73.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | Data science in action |
| Thesis Supervisor: | Martino, Alessio |
| Thesis Co-Supervisor: | Spagnoletti, Paolo |
| Academic Year: | 2022/2023 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 22 Apr 2024 14:15 |
| Last Modified: | 22 Apr 2024 14:15 |
| URI: | https://tesi.luiss.it/id/eprint/38500 |
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