Cozzolino, Giovanni (2018) A semantic methodology for (un)structured digital evidences analysis. [Tesi di dottorato]

[img]
Preview
Text
Cozzolino_Giovanni_XXXI.pdf

Download (2MB) | Preview
[error in script] [error in script]
Item Type: Tesi di dottorato
Lingua: English
Title: A semantic methodology for (un)structured digital evidences analysis
Creators:
CreatorsEmail
Cozzolino, Giovannigiovanni.cozzolino@unina.it
Date: November 2018
Number of Pages: 144
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Elettrica e delle Tecnologie dell'Informazione
Dottorato: Information technology and electrical engineering
Ciclo di dottorato: 31
Coordinatore del Corso di dottorato:
nomeemail
Riccio, Danieledaniele.riccio@unina.it
Tutor:
nomeemail
Mazzeo, AntoninoUNSPECIFIED
Amato, FloraUNSPECIFIED
Date: November 2018
Number of Pages: 144
Uncontrolled Keywords: semantic computer digital forensic correlation
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 - Sistemi di elaborazione delle informazioni
Date Deposited: 22 Jan 2019 22:15
Last Modified: 30 Jun 2020 09:07
URI: http://www.fedoa.unina.it/id/eprint/12687

Abstract

Nowadays, more than ever, digital forensics activities are involved in any criminal, civil or military investigation and represent a fundamental tool to support cyber-security. Investigators use a variety of techniques and proprietary software forensic applications to examine the copy of digital devices, searching hidden, deleted, encrypted, or damaged files or folders. Any evidence found is carefully analysed and documented in a "finding report" in preparation for legal proceedings that involve discovery, depositions, or actual litigation. The aim is to discover and analyse patterns of fraudulent activities. In this work, a new methodology is proposed to support investigators during the analysis process, correlating evidences found through different forensic tools. The methodology was implemented through a system able to add semantic assertion to data generated by forensics tools during extraction processes. These assertions enable more effective access to relevant information and enhanced retrieval and reasoning capabilities.

Actions (login required)

View Item View Item