Privacy-Preserving Data Integration for Recidivism Assessment
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.
Authors
- Sonia Bergamaschi (ORCID: https://orcid.org/0000-0001-8087-6587)
- Domenico Beneventano (ORCID: https://orcid.org/0000-0001-6616-1753)
- Lisa Trigiante (ORCID: https://orcid.org/0000-0002-2021-9259)
Institutions
- University of Modena and Reggio Emilia (IT)
Publication Details
- Journal
- International Journal of Computer Applications
- Published
- 2025-06-20
- DOI
- https://doi.org/10.5120/ijca2025925080
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 0.00