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Vishing: detecting social engineering in spoken communication — a first survey & urgent roadmap to address an emerging societal challenge

  • Vishing – the use of voice calls for phishing – is a form of Social Engineering (SE) attacks. The latter have become a pervasive challenge in modern societies, with over 300,000 yearly victims in the US alone. An increasing number of those attacks is conducted via voice communication, be it through machine-generated ‘robocalls’ or human actors. The goals of ‘social engineers’ can be manifold, from outright fraud to more subtle forms of persuasion. Accordingly, social engineers adopt multi-faceted strategies for voice-based attacks, utilising a variety of ‘tricks’ to exert influence and achieve their goals. Importantly, while organisations have set in place a series of guardrails against other types of SE attacks, voice calls still remain ‘open ground’ for potential bad actors. In the present contribution, we provide an overview of the existing speech technology subfields that need to coalesce into a protective net against one of the major challenges to societies worldwide. Given theVishing – the use of voice calls for phishing – is a form of Social Engineering (SE) attacks. The latter have become a pervasive challenge in modern societies, with over 300,000 yearly victims in the US alone. An increasing number of those attacks is conducted via voice communication, be it through machine-generated ‘robocalls’ or human actors. The goals of ‘social engineers’ can be manifold, from outright fraud to more subtle forms of persuasion. Accordingly, social engineers adopt multi-faceted strategies for voice-based attacks, utilising a variety of ‘tricks’ to exert influence and achieve their goals. Importantly, while organisations have set in place a series of guardrails against other types of SE attacks, voice calls still remain ‘open ground’ for potential bad actors. In the present contribution, we provide an overview of the existing speech technology subfields that need to coalesce into a protective net against one of the major challenges to societies worldwide. Given the dearth of speech science and technology works targeting this issue, we have opted for a narrative review that bridges the gap between the existing psychological literature on the topic and research that has been pursued in parallel by the speech community on some of the constituent constructs. Our review reveals that very little literature exists on addressing this very important topic from a speech technology perspective, an omission further exacerbated by the lack of available data. Thus, our main goal is to highlight this gap and sketch out a roadmap to mitigate it, beginning with the psychological underpinnings of vishing, which primarily include deception and persuasion strategies, continuing with the speech-based approaches that can be used to detect those, as well as the generation and detection of AI-based vishing attempts, and close with a discussion of ethical and legal considerations.show moreshow less

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Metadaten
Author:Andreas TriantafyllopoulosORCiD, Anika A. Spiesberger, Iosif Tsangko, Xin Jing, Verena Distler, Felix Dietz, Florian Alt, Björn W. SchullerORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1217345
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/121734
ISSN:0885-2308OPAC
Parent Title (English):Computer Speech & Language
Publisher:Elsevier BV
Place of publication:Amsterdam
Type:Article
Language:English
Year of first Publication:2025
Publishing Institution:Universität Augsburg
Release Date:2025/05/05
Volume:94
First Page:101802
DOI:https://doi.org/10.1016/j.csl.2025.101802
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Embedded Intelligence for Health Care and Wellbeing
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):CC-BY-NC-ND 4.0: Creative Commons: Namensnennung - Nicht kommerziell - Keine Bearbeitung (mit Print on Demand)