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Privacy-Preserving Data Integration for Recidivism Assessment

by Lisa Trigiante, Domenico Beneventano, Sonia Bergamaschi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 13
Year of Publication: 2025
Authors: Lisa Trigiante, Domenico Beneventano, Sonia Bergamaschi
10.5120/ijca2025925080

Lisa Trigiante, Domenico Beneventano, Sonia Bergamaschi . Privacy-Preserving Data Integration for Recidivism Assessment. International Journal of Computer Applications. 187, 13 ( Jun 2025), 1-8. DOI=10.5120/ijca2025925080

@article{ 10.5120/ijca2025925080,
author = { Lisa Trigiante, Domenico Beneventano, Sonia Bergamaschi },
title = { Privacy-Preserving Data Integration for Recidivism Assessment },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2025 },
volume = { 187 },
number = { 13 },
month = { Jun },
year = { 2025 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number13/privacy-preserving-data-integration-for-recidivism-assessment/ },
doi = { 10.5120/ijca2025925080 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-06-21T01:57:02.418353+05:30
%A Lisa Trigiante
%A Domenico Beneventano
%A Sonia Bergamaschi
%T Privacy-Preserving Data Integration for Recidivism Assessment
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 13
%P 1-8
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The emergence of Digital Justice in conjunction with advanced Data Analysis techniques presents the opportunity to advance the criminal justice system toward an innovative Data-Driven approach. An important issue of public safety is the analysis of legal recidivism. Assessing recidivism is a complex measurement problem that necessitates reconstructing a subject’s criminal history from criminal records, which usually reside in different autonomous databases. In addition, the collection and processing of sensitive legal-related data about individuals imposes consideration of privacy legislation and confidentiality implications. This paper presents the design and development of a Proof of Concept (PoC) for a Privacy-Preserving Data Integration (PPDI) framework to establish a Data Warehouse across criminal and court sources within the Italian Justice Domain and a Data Mart to assess the recidivism phenomena.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Integration GDPR Privacy Pseudonym Justice Domain

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