INSPECTr

The principal objective of INSPECTr (Intelligence Network and Secure Platform for Evidence Correlation and Transfer) was to develop a shared intelligent platform and a novel process for gathering, analysing, prioritizing and presenting key data. This data could be used to help in the prediction, detection and management of crime in support of multiple agencies at local and (inter)national level. The data originated from the outputs of free and commercial digital forensic tools complemented by online resource gathering. Using both structured and unstructured data as input, the developed platform facilitated the ingestion and homogenisation of this data with increased levels of automatisation, allowing for interoperability between outputs from multiple data formats.

Various knowledge discovery techniques allowed the investigator to visualise and bookmark important evidential material and export it to an investigative report. In addition to providing basic and advanced (cognitive) crosscorrelation analysis with existing case data, this technique aimed to improve knowledge discovery across exhibit analysis within a case, between separate cases and ultimately, between interjurisdictional investigations.

INSPECTr depolyed big data analytics, cognitive machine learning and blockchain approaches to significantly improve digital and forensics capabilities for pan-European LEAs. It intended to reduce the complexity and the costs in law enforcement agencies and related actors to use leading edge analytical tools proportionally and in line with relevant legislation (including fundamental rights).

Duration of the project

2019 - 2022

Awarded grant

6,997,910 euros (of which 261,250 euros for the UG), obtained from Horizon 2020

Contact persons at our Faculty

Prof. G.P. (Jeanne) Mifsud Bonnici
Mr. M. (Melania) Tudorica

Websites with additional information