Classification of network traffic within cryptographically secure channels using deep neural networks
Lizzit, Michele (A.A. 2020/2021) Classification of network traffic within cryptographically secure channels using deep neural networks. Tesi di Laurea in Artificial intelligence and machine learning, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 44. [Bachelor's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Cryptographic systems and encryption. Historic introduction on cryptography. What is cryptography. What is cryptanalysis. The role of encryption in data protection. TLS and PKI. Cyber attacks. Common cyber attacks. Side channel attacks. Timing attacks. Encrypted traffic analysis. Mitigations against side channel attacks. AiI and machine learning. Deep learning. Deep learning in timing attacks. Big data. A concrete implementation. Extraction of information from secure network traffic. Size and timing information. Analysis workflow. Training dataset. Data preprocessing. Application classification. Human-bot discrimination.
References
Bibliografia e sitografia: pp. 42-43.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Artificial intelligence and machine learning |
| Thesis Supervisor: | Italiano, Giuseppe Francesco |
| Academic Year: | 2020/2021 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 21 Oct 2021 13:24 |
| Last Modified: | 21 Oct 2021 13:24 |
| URI: | https://tesi.luiss.it/id/eprint/30501 |
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