polito.it
Politecnico di Torino (logo)

Clustering of categorical data for anonymization and anomaly detection

Cappuzzo, Riccardo

Clustering of categorical data for anonymization and anomaly detection.

Rel. Elena Maria Baralis. Politecnico di Torino, Corso di laurea magistrale in Communications And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni), 2018

[img]
Preview
PDF (Tesi_di_laurea) - Tesi
Document access: Anyone
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (1MB) | Preview
Abstract:

The thesis reports the studies performed to improve the ROCK clustering algorithm together with its applications in the anonymization and anomaly detection fields. Various changes to the original algorithm are introduced and the algorithm itself is employed in a novel environment to achieve better anonymization results.

Relators: Elena Maria Baralis
Academic year: 2017/18
Publication type: Electronic
Number of Pages: 74
Subjects:
Corso di laurea: Corso di laurea magistrale in Communications And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni)
Classe di laurea: New organization > Master science > LM-27 - TELECOMMUNICATIONS ENGINEERING
Ente in cotutela: EURECOM - Telecom Paris Tech (FRANCIA)
Aziende collaboratrici: SAP Labs France
URI: http://webthesis.biblio.polito.it/id/eprint/7571
Modify record (reserved for operators) Modify record (reserved for operators)