AI-Driven Vishing Attacks: A Practical Approach
Today, there are many security problems at the technological level, especially in telecommunications. Cybercriminals invade and steal data from any system using vector attacks such as phishing through scam mail, fake websites and phone calls. This latter form of phishing is called vishing (phishing...
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MDPI AG
2024-11-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/77/1/15 |
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| author | Fabricio Toapanta Belén Rivadeneira Christian Tipantuña Danny Guamán |
| author_facet | Fabricio Toapanta Belén Rivadeneira Christian Tipantuña Danny Guamán |
| author_sort | Fabricio Toapanta |
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| description | Today, there are many security problems at the technological level, especially in telecommunications. Cybercriminals invade and steal data from any system using vector attacks such as phishing through scam mail, fake websites and phone calls. This latter form of phishing is called vishing (phishing using voice). Through vishing and using social engineering techniques, attackers can impersonate family members or friends of potential victims and obtain information or money or a specific target objective. Traditionally, to carry out vishing attacks, attackers imitated the vocabulary, voice and tone of a person known to the victim. However, with current artificial intelligence (AI) tools, obtaining synthetic voices similar or identical to the person to be impersonated is more straightforward and precise. In this regard, this paper, using ChatGPT and three AI-enabled applications for voice synthesis presents a practical approach for deploying vishing attacks in an academic environment to identify the limitations, implications and possible countermeasures to mitigate the effects on Internet users. Results demonstrate the effectiveness of vishing attacks, and the maturity level of the employed AI tools. |
| format | Article |
| id | doaj-art-fb78b87fc60a401596940bdf5a5fa1d6 |
| institution | OA Journals |
| issn | 2673-4591 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-fb78b87fc60a401596940bdf5a5fa1d62025-08-20T02:00:22ZengMDPI AGEngineering Proceedings2673-45912024-11-017711510.3390/engproc2024077015AI-Driven Vishing Attacks: A Practical ApproachFabricio Toapanta0Belén Rivadeneira1Christian Tipantuña2Danny Guamán3Facultad de Ingeniería Eléctrica y Electrónica, Escuela Politécnica Nacional, Quito 170525, EcuadorFacultad de Ingeniería Eléctrica y Electrónica, Escuela Politécnica Nacional, Quito 170525, EcuadorFacultad de Ingeniería Eléctrica y Electrónica, Escuela Politécnica Nacional, Quito 170525, EcuadorFacultad de Ingeniería Eléctrica y Electrónica, Escuela Politécnica Nacional, Quito 170525, EcuadorToday, there are many security problems at the technological level, especially in telecommunications. Cybercriminals invade and steal data from any system using vector attacks such as phishing through scam mail, fake websites and phone calls. This latter form of phishing is called vishing (phishing using voice). Through vishing and using social engineering techniques, attackers can impersonate family members or friends of potential victims and obtain information or money or a specific target objective. Traditionally, to carry out vishing attacks, attackers imitated the vocabulary, voice and tone of a person known to the victim. However, with current artificial intelligence (AI) tools, obtaining synthetic voices similar or identical to the person to be impersonated is more straightforward and precise. In this regard, this paper, using ChatGPT and three AI-enabled applications for voice synthesis presents a practical approach for deploying vishing attacks in an academic environment to identify the limitations, implications and possible countermeasures to mitigate the effects on Internet users. Results demonstrate the effectiveness of vishing attacks, and the maturity level of the employed AI tools.https://www.mdpi.com/2673-4591/77/1/15cybersecurityChatGPTsocial engineeringartificial intelligenceLLMvishing |
| spellingShingle | Fabricio Toapanta Belén Rivadeneira Christian Tipantuña Danny Guamán AI-Driven Vishing Attacks: A Practical Approach Engineering Proceedings cybersecurity ChatGPT social engineering artificial intelligence LLM vishing |
| title | AI-Driven Vishing Attacks: A Practical Approach |
| title_full | AI-Driven Vishing Attacks: A Practical Approach |
| title_fullStr | AI-Driven Vishing Attacks: A Practical Approach |
| title_full_unstemmed | AI-Driven Vishing Attacks: A Practical Approach |
| title_short | AI-Driven Vishing Attacks: A Practical Approach |
| title_sort | ai driven vishing attacks a practical approach |
| topic | cybersecurity ChatGPT social engineering artificial intelligence LLM vishing |
| url | https://www.mdpi.com/2673-4591/77/1/15 |
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