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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F26%3A0196783" target="_blank" >RIV/00216305:26230/26:0196783 - isvavai.cz</a>

  • Result on the web

    <a href="https://publications.idiap.ch/attachments/papers/2024/Rangappa_EAIICDF2C2024_2024.pdf" target="_blank" >https://publications.idiap.ch/attachments/papers/2024/Rangappa_EAIICDF2C2024_2024.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-89363-6_20" target="_blank" >10.1007/978-3-031-89363-6_20</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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 paperpresents 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 theidentification of offenders involved in serious and organized crime.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the15th EAI International Conference on Digital Forensics & Cyber Crime (EAI-ICDF2C24)

  • ISBN

  • ISSN

    1867-8211

  • e-ISSN

    1867-822X

  • Number of pages

    14

  • Pages from-to

    340-353

  • Publisher name

    SPRINGER INTERNATIONAL PUBLISHING AGGEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

  • Place of publication

    Dubrovnik

  • Event location

    Dubrovnik

  • Event date

    Oct 9, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001571204500020