Publication Details

Detecting Criminal Networks via Non-Content Communication Data Analysis Techniques from the TRACY Project

RANGAPPA Pradeep, MUSCAT Amanda, SANCHEZ-LARA Alejandra, MOTLÍČEK Petr, ANTONOPOULOU Michaela, FOURFOURIS Ioannis, SKARLATOS Antonios, AVGERINOS Nikos, TSANGARIS Manolis and KOSTKA Kasia. Detecting Criminal Networks via Non-Content Communication Data Analysis Techniques from the TRACY Project. In: Proceedings of the15th EAI International Conference on Digital Forensics & Cyber Crime (EAI-ICDF2C24). Dubrovnik, 2024, pp. 1-15. Available from: https://publications.idiap.ch/attachments/papers/2024/Rangappa_EAIICDF2C2024_2024.pdf
Type
conference paper
Language
english
Authors
Rangappa Pradeep (IDIAP)
Muscat Amanda (IDIAP)
Sanchez-lara Alejandra (IDIAP)
Motlíček Petr, doc. Ing., Ph.D. (DCGM FIT BUT)
Antonopoulou Michaela (PERFORMANCE)
Fourfouris Ioannis (PERFORMANCE)
Skarlatos Antonios (PERFORMANCE)
Avgerinos Nikos (PERFORMANCE)
Tsangaris Manolis (PERFORMANCE)
Kostka Kasia (TIMELEX)
URL
Keywords

Law Enforcement Agencies, Suspect DetectionNon-Content Data, Social Influence Analysis, Link Prediction

Abstract

This paper explores the critical role of non-content data
(NCD), provided by electronic communications service providers in aiding criminal investigations. As highlighted by the Law Enforcement Agencies (LEAs) and the European Commission, NCD plays a fundamental role in identifying suspects and discerning behavioral patterns. Despite its significance, LEAs encounter various challenges in effectively analyzing the extensive volume of NCD. To address this issue, this paper
presents the importance of (although simulated but realistic) data collection, the technologies that can be built and the methods for detecting the suspect within the framework of the TRACY project. These techniques aim to enhance capabilities of LEAs by processing large-scale NCD and aligning it with existing evidence. By prioritizing the tracing of suspects movements and integrating data from diverse NCD sources, TRACY's initial approach on synthetic data promises to significantly advance the
identification of offenders involved in serious and organized crime.

Published
2024
Pages
1-15
Proceedings
Proceedings of the15th EAI International Conference on Digital Forensics & Cyber Crime (EAI-ICDF2C24)
Conference
EAI ICDF2C 2024 - 15th EAI International Conference on Digital Forensics & Cyber Crime, Dubrovnik, HR
Place
Dubrovnik, HR
BibTeX 
@INPROCEEDINGS{FITPUB13373,
   author = "Pradeep Rangappa and Amanda Muscat and Alejandra Sanchez-lara and Petr Motl\'{i}\v{c}ek and Michaela Antonopoulou and Ioannis Fourfouris and Antonios Skarlatos and Nikos Avgerinos and Manolis Tsangaris and Kasia Kostka",
   title = "Detecting Criminal Networks via Non-Content Communication Data Analysis Techniques from the TRACY Project",
   pages = "1--15",
   booktitle = "Proceedings of the15th EAI International Conference on Digital Forensics \& Cyber Crime (EAI-ICDF2C24)",
   year = 2024,
   location = "Dubrovnik, HR",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/13373"
}
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