PORTALE DELLA DIDATTICA

Ricerca CERCA
  KEYWORD

SmartData@PoliTO

Tesi al Politecnico

Generalizable language models for network measurement and cybersecurity​

Parole chiave AI, CYBERSECURITY, FIREWALL, LLM, MACHINE LEARNING

Riferimenti MARCO MELLIA, LUCA VASSIO

Riferimenti esterni Idilio Drago - Unito - idilio.drago@unito.it

Gruppi di ricerca DATABASE AND DATA MINING GROUP - DBDM, SmartData@PoliTO, Telecommunication Networks Group

Descrizione Firewall/IPS and EDR and Cloud security services analyze huge amounts of structured data to detect and classify threats, mainly based on human-written rules.​

The thesis goal is to understand if lightweight and generalizable language models can extract insights from raw data. A key objective is to ensure generalization abilities beyond syntactic heuristics. A possible solution is to create multi-modal embeddings to conceptually constrain the embeddings towards the right task. ​

Thesis Goal​

- Propose techniques based on language models for identify network traffic threats​

- Ensure generalization beyond simple rule by crafting proper training and validation data​

- Use techniques based on multi-modal embeddings (similar to OpenAI CLIP) ​

Conoscenze richieste - Good programming skills (such as Python and Spark)
- Machine Learning knowledge (such as Torch, Tensorflow)
- Basics of NLP
- Basics of Networking and security

Note A GPA of at least 27/30 is preferred.
Possible graduation prize of 2000 euros.


Scadenza validita proposta 14/01/2026      PROPONI LA TUA CANDIDATURA