DeepDetection: Privacy-Enhanced Deep Voice Detection and User Authentication for Preventing Voice Phishing
The deep voice detection technology currently being researched causes personal information leakage because the input voice data are stored in the detection server. To overcome this problem, in this paper, we propose a novel system (i.e., DeepDetection) that can detect deep voices and authenticate us...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/21/11109 |
| _version_ | 1797469193213313024 |
|---|---|
| author | Yeajun Kang Wonwoong Kim Sejin Lim Hyunji Kim Hwajeong Seo |
| author_facet | Yeajun Kang Wonwoong Kim Sejin Lim Hyunji Kim Hwajeong Seo |
| author_sort | Yeajun Kang |
| collection | DOAJ |
| description | The deep voice detection technology currently being researched causes personal information leakage because the input voice data are stored in the detection server. To overcome this problem, in this paper, we propose a novel system (i.e., DeepDetection) that can detect deep voices and authenticate users without exposing voice data to the server. Voice phishing prevention is achieved in two-way approaches by performing primary verification through deep voice detection and secondary verification of whether the sender is the correct sender through user authentication. Since voice preprocessing is performed on the user local device, voice data are not stored on the detection server. Thus, we can overcome the security vulnerabilities of the existing detection research. We used ASVspoof 2019 and achieved an F1-score of 100% in deep voice detection and an F1 score of 99.05% in user authentication. Additionally, the average EER for user authentication achieved was 0.15. Therefore, this work can be effectively used to prevent deep voice-based phishing. |
| first_indexed | 2024-03-09T19:16:59Z |
| format | Article |
| id | doaj.art-4ba4ebfb95f34271a17d2c8b5dd9e523 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T19:16:59Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4ba4ebfb95f34271a17d2c8b5dd9e5232023-11-24T03:38:08ZengMDPI AGApplied Sciences2076-34172022-11-0112211110910.3390/app122111109DeepDetection: Privacy-Enhanced Deep Voice Detection and User Authentication for Preventing Voice PhishingYeajun Kang0Wonwoong Kim1Sejin Lim2Hyunji Kim3Hwajeong Seo4Division of IT Convergence Engineering, Hansung University, Seoul 02876, KoreaDivision of IT Convergence Engineering, Hansung University, Seoul 02876, KoreaDivision of IT Convergence Engineering, Hansung University, Seoul 02876, KoreaDivision of IT Convergence Engineering, Hansung University, Seoul 02876, KoreaDivision of IT Convergence Engineering, Hansung University, Seoul 02876, KoreaThe deep voice detection technology currently being researched causes personal information leakage because the input voice data are stored in the detection server. To overcome this problem, in this paper, we propose a novel system (i.e., DeepDetection) that can detect deep voices and authenticate users without exposing voice data to the server. Voice phishing prevention is achieved in two-way approaches by performing primary verification through deep voice detection and secondary verification of whether the sender is the correct sender through user authentication. Since voice preprocessing is performed on the user local device, voice data are not stored on the detection server. Thus, we can overcome the security vulnerabilities of the existing detection research. We used ASVspoof 2019 and achieved an F1-score of 100% in deep voice detection and an F1 score of 99.05% in user authentication. Additionally, the average EER for user authentication achieved was 0.15. Therefore, this work can be effectively used to prevent deep voice-based phishing.https://www.mdpi.com/2076-3417/12/21/11109voice phishingdeep voice detectionuser authenticationprivacy preservationautoencoderconvolutional neural networks |
| spellingShingle | Yeajun Kang Wonwoong Kim Sejin Lim Hyunji Kim Hwajeong Seo DeepDetection: Privacy-Enhanced Deep Voice Detection and User Authentication for Preventing Voice Phishing Applied Sciences voice phishing deep voice detection user authentication privacy preservation autoencoder convolutional neural networks |
| title | DeepDetection: Privacy-Enhanced Deep Voice Detection and User Authentication for Preventing Voice Phishing |
| title_full | DeepDetection: Privacy-Enhanced Deep Voice Detection and User Authentication for Preventing Voice Phishing |
| title_fullStr | DeepDetection: Privacy-Enhanced Deep Voice Detection and User Authentication for Preventing Voice Phishing |
| title_full_unstemmed | DeepDetection: Privacy-Enhanced Deep Voice Detection and User Authentication for Preventing Voice Phishing |
| title_short | DeepDetection: Privacy-Enhanced Deep Voice Detection and User Authentication for Preventing Voice Phishing |
| title_sort | deepdetection privacy enhanced deep voice detection and user authentication for preventing voice phishing |
| topic | voice phishing deep voice detection user authentication privacy preservation autoencoder convolutional neural networks |
| url | https://www.mdpi.com/2076-3417/12/21/11109 |
| work_keys_str_mv | AT yeajunkang deepdetectionprivacyenhanceddeepvoicedetectionanduserauthenticationforpreventingvoicephishing AT wonwoongkim deepdetectionprivacyenhanceddeepvoicedetectionanduserauthenticationforpreventingvoicephishing AT sejinlim deepdetectionprivacyenhanceddeepvoicedetectionanduserauthenticationforpreventingvoicephishing AT hyunjikim deepdetectionprivacyenhanceddeepvoicedetectionanduserauthenticationforpreventingvoicephishing AT hwajeongseo deepdetectionprivacyenhanceddeepvoicedetectionanduserauthenticationforpreventingvoicephishing |