On the Use of Heterogeneous Graph Neural Networks for Detecting Malicious Activities: a Case Study with Cryptocurrencies Article Swipe
Stefano Ferretti
,
Gabriele D’Angelo
,
Vittorio Ghini
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3677117.3685009
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3677117.3685009
This paper presents a study on the application of Heterogeneous Graph Neural Networks (HGNNs) for enhancing the security of complex social systems by identifying illicit and malicious behaviors. We focus on digital asset tokenization, a key component in the construction of many innovative social services, with the aim of classifying token exchanges and identifying illicit activities. Utilizing the Elliptic++ dataset, we demonstrate the efficacy of HGNNs in identifying illicit activities in token-based exchanging applications. In particular, we evaluate four different HGNN architectures, i.e. Heterogeneous GAT, Heterogeneous SAGE, HGT (Heterogeneous Graph Transformer), and HAN (Heterogeneous Attention Network). Our results underscore the importance of characterizing and describing interactions in these complex systems, both for studying the system dynamics and for activating mechanisms to cope with cybersecurity issues, like misuses and usurpation of resources in social systems.
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- OA Status
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https://openalex.org/W4401837637Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3677117.3685009Digital Object Identifier
- Title
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On the Use of Heterogeneous Graph Neural Networks for Detecting Malicious Activities: a Case Study with CryptocurrenciesWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-08-24Full publication date if available
- Authors
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Stefano Ferretti, Gabriele D’Angelo, Vittorio GhiniList of authors in order
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https://doi.org/10.1145/3677117.3685009Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1145/3677117.3685009Direct OA link when available
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Cryptocurrency, Computer science, Graph, Artificial neural network, Artificial intelligence, Theoretical computer science, Computer security, Machine learningTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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17Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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