[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content
Springer Nature Link
Log in

Research Agenda for Speaker Authentication

  • Conference paper
  • First Online:
Human Aspects of Information Security and Assurance (HAISA 2024)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 721))

  • 32 Accesses

Abstract

In this study, we thoroughly examined every component of speaker authentication, analyzing the input, process, and output phases to identify flaws and new threats. Our investigation is organized around specific research topics that aim to effectively address and minimize the identified dangers. By methodically exploring each component of the speaker authentication process, we not only identify possible issues but also recommend proactive methods to protect these systems from unauthorized access. Our research questions act as significant probes, allowing for a deeper knowledge of the underlying difficulties and leading to the creation of tailored authentication solutions. This study goes beyond theoretical analysis and provides practical insights and strategic recommendations for improving the security and reliability of speaker authentication systems in a variety of sectors, including cybersecurity and forensic analysis. We highlight the interrelated nature of the input, process, and output stages, emphasizing the importance of remaining vigilant in the face of emerging security risks. Our goal is to provide the necessary knowledge and tools to effectively handle the complexities of speaker authentication in the changing digital world. This work establishes a solid foundation for the development of safe and durable speaker authentication methods.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 64.99
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
GBP 79.99
Price includes VAT (United Kingdom)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Anwer, H., Anjum, S., Saqib, N.A.: Robust speaker recognition for E-commerce system. In: International Conference on Radar, Antenna, Microwave, Electronics and Telecommunications, pp. 92–97 (2015). https://doi.org/10.1109/ICRAMET.2015.7380781, nULL

  2. Araujo, T., Helberger, N., Kruikemeier, S., de Vreese, C.H.: In AI we trust? perceptions about automated decision-making by artificial intelligence. AI and Society 35, 611–623 (2020). https://doi.org/10.1007/s00146-019-00931-w

  3. Arp, D., et al.: Dos and don’ts of machine learning in computer security. In: Proceedings of USENIX Security Symposium (2022)

    Google Scholar 

  4. Bhugra, D., McKenzie, K.: Expressed emotion across cultures. Adv. Psychiatric Treatment 9, 342–348 (2003). https://doi.org/10.1192/apt.9.5.342

  5. Bibi, K., Naz, S., Rehman, A.: Biometric signature authentication using machine learning techniques: Current trends, challenges and opportunities. Multimedia Tools Appli. 79, 289–340 (2020). https://doi.org/10.1007/s11042-019-08022-0

  6. Bodepudi, A., Reddy, M.: Spoofing attacks and mitigation strategies in biometrics-as-a-service systems. Eigenpub Rev. Sci. Technol. 4, 1–14 (2020)

    Google Scholar 

  7. Ciarrochi, J., Scott, G., Deane, F.P., Heaven, P.C.: Relations between social and emotional competence and mental health: a construct validation study. Personality Individual Differences 35, 1947–1963 (12003). https://doi.org/10.1016/S0191-8869(03)00043-6

  8. Duan, S., Zhang, J., Roe, P., Towsey, M.: A survey of tagging techniques for music, speech and environmental sound. Artifi. Intell. Rev. 42, 637–661 (2014) https://doi.org/10.1007/s10462-012-9362-y

  9. Fatin, I., Zulkifli, D.B., Fuad, N., Marwan, M.E.: An application of biometric security identification for automated teller machine. ACCESS Online J. IJACSSE-Inter. J. Adv. Comput. Syst. Softw. Eng. 1, 6–11 (2020)

    Google Scholar 

  10. Galvez, D., et al.: The people’s speech: A large-scale diverse english speech recognition dataset for commercial usage. arXiv preprint arXiv:2111.09344 (2021)

  11. Hancock, J.T., Landrigan, C., Silver, C.: Expressing emotion in text-based communication, pp. 929–932 (2007). https://doi.org/10.1145/1240624.1240764

  12. Hizlisoy, S., Arslan, R.S.: Text independent speaker recognition based on MFCC and machine learning. Selcuk Univ. J. Eng. Sci. 20, 73–078 (2021). http://sujes.selcuk.edu.tr

  13. Jiang, P., et al.: Securing liveness detection for voice authentication via Pop Noises. IEEE Trans. Dependable Sec. Comput. 20, 1702–1718 (2023). https://doi.org/10.1109/TDSC.2022.3163024

  14. Jürgens, R., Grass, A., Drolet, M., Fischer, J.: Effect of acting experience on emotion expression and recognition in voice: non-actors provide better stimuli than expected. J. Nonverbal Behav. 39, 195–214 (2015). https://doi.org/10.1007/s10919-015-0209-5

  15. Kaplan, R.M., Chambers, D.A., Glasgow, R.E.: Big data and large sample size: a cautionary note on the potential for bias (2014). https://doi.org/10.1111/cts.12178

  16. Khokher, R., Singh, R.C.: Footprint Identification: Review of an Emerging Biometric Trait. Macromolecular Symposia 397 (2021). https://doi.org/10.1002/masy.202000246

  17. Lindebaum, D., Jordan, P.J.: Positive emotions, negative emotions, or utility of discrete emotions? J. Organizat. Behav. 33, 1027–1030 (2012). https://doi.org/10.1002/job.1819

  18. Lumini, A., Nanni, L.: Overview of the combination of biometric matchers. Inform. Fus. 33, 71–85 (2017). https://doi.org/10.1016/j.inffus.2016.05.003

    Article  Google Scholar 

  19. Mau, T.L., et al.: Professional actors demonstrate variability, not stereotypical expressions, when portraying emotional states in photographs. Nat. Commun. 12 (2021).https://doi.org/10.1038/s41467-021-25352-6

  20. Moreno, J.D., Martínez-Huertas, J., Olmos, R., Jorge-Botana, G., Botella, J.: Can personality traits be measured analyzing written language? a meta-analytic study on computational methods. Personal. Individual Differences 177 (2021). https://doi.org/10.1016/j.paid.2021.110818

  21. Nam, H., Kim, S.H., Park, Y.H.: FilterAugment: an acoustic environmental data augmentation method, vol. 2022, pp. 4308–4312. Institute of Electrical and Electronics Engineers Inc. (May 2022) https://doi.org/10.1109/ICASSP43922.2022.9747680

  22. Naveen, R., Reddy, C.J., Tanguturu, R., Kumar, M.A.: Speaker identification and verification using deep learning. Instit. Electr. Electr. En. Inc. (2022). https://doi.org/10.1109/ICoNSIP49665.2022.10007520

  23. Pal, K., Patel, B.V.: Data Classification with k-fold Cross Validation and Holdout Accuracy Estimation Methods with 5 Different Machine Learning Techniques, pp. 83–87. Institute of Electrical and Electronics Engineers Inc. (Mar 2020). https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00016

  24. Pandey, L., Arif, A.S.: Silent Speech and Emotion Recognition from Vocal Tract Shape Dynamics in Real-Time MRI, pp. 1–8 (8 2021). http://arxiv.org/abs/2106.08706

  25. Patel, Y., et al.: Deepfake generation and detection: case study and challenges. IEEE Access 11, 143296–143323 (2023). https://doi.org/10.1109/ACCESS.2023.3342107

    Article  Google Scholar 

  26. Pranto, S.I., et al.: AIMS TALK: Intelligent Call Center Support in Bangla Language with Speaker Authentication. Institute of Electrical and Electronics Engineers Inc. (2021). https://doi.org/10.1109/ETCCE54784.2021.9689831

  27. Ramezan, C.A., Warner, T.A., Maxwell, A.E., Price, B.S.: Effects of training set size on supervised machine-learning land-cover classification of large-area high-resolution remotely sensed data. Remote Sensing 13, 1–27 (2021). https://doi.org/10.3390/rs13030368

  28. Salehi, A.W., et al.: A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope ( Apr 2023).https://doi.org/10.3390/su15075930

  29. Schirmer, A., Adolphs, R.: Emotion perception from face, voice, and touch: comparisons and convergence. Trends Cognitive Sci. 21, 216–228 (2017). https://doi.org/10.1016/j.tics.2017.01.001, https://doi.org/10.1016/j.tics.2017.01.001

  30. Shrestha, Y.R., Ben-Menahem, S.M., von Krogh, G.: Organizational decision-making structures in the age of artificial intelligence. California Mana. Rev. 66–83 (2019). https://doi.org/10.1177/0008125619862257

  31. Singh, M., Pati, D.: Countermeasures to Replay Attacks: A Review. IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India) 37, 599–614 (2020). https://doi.org/10.1080/02564602.2019.1684851

  32. Story, B.H., et al.: An age-dependent vocal tract model for males and females based on anatomic measurements 3079 (2018). https://doi.org/10.1121/1.5038264

  33. Szijjarto, L., Bereczkei, T.: The machiavellians’ “cool syndrome”: they experience intensive feelings but have difficulties in expressing their emotions. Current Psychol. 34, 363–375 (2015).https://doi.org/10.1007/s12144-014-9262-1

  34. Taylor, S., Dromey, C., Nissen, S.L., Tanner, K., Eggett, D., Corbin-Lewis, K.: Age-related changes in speech and voice: spectral and cepstral measures. J. Speech, Lang. Hearing Res. 63, 647–660 (2020). https://doi.org/10.1044/2019_JSLHR-19-00028

  35. Turgeman, A., Zelazny, F.: Invisible challenges: the next step in behavioural biometrics?. Biometric Technol. Today 2017, 5–7 (2017). https://doi.org/10.1016/S0969-4765(17)30114-5

  36. Wang, Q., Wang, M., Yang, Y., Zhang, X.: Multi-modal emotion recognition using EEG and speech signals. Comput. Biol. Med. 149 (2022). https://doi.org/10.1016/j.compbiomed.2022.105907

  37. Wells, A., Usman, A.B.: Privacy and biometrics for smart healthcare systems: attacks, and techniques. Information Security J. (2023). https://doi.org/10.1080/19393555.2023.2260818

    Article  Google Scholar 

  38. Wu, L., Yang, J., Zhou, M., Chen, Y., Wang, Q.: LVID: a multimodal biometrics authentication system on smartphones. IEEE Trans. Inf. Forensics Secur. 15, 1572–1585 (2020). https://doi.org/10.1109/TIFS.2019.2944058

    Article  Google Scholar 

  39. Yang, W., Wang, S., Hu, J., Zheng, G., Valli, C.: Security and accuracy of fingerprint-based biometrics: a review. Symmetry 11 (2019).https://doi.org/10.3390/sym11020141

  40. Zloteanu, M., Krumhuber, E.G.: Expression Authenticity: The Role of Genuine and Deliberate Displays in Emotion Perception. Front. Psychol. 11 (1 2021) https://doi.org/10.3389/fpsyg.2020.611248

  41. Özaydın, S.: Examination of energy based voice activity detection algorithms for noisy speech signals. Euro. J. Sci. Technol., pp. 157–163 (2019). https://doi.org/10.31590/ejosat.637741

Download references

Author information

Authors and Affiliations

  1. School of IT, Nelson Mandela University, Gqeberha, South Africa

    Ebenhaeser Janse van Rensburg, Reinhardt A. Botha & Bertram Haskins

  2. Noroff University College, Oslo, Norway

    Reinhardt A. Botha & Bertram Haskins

Authors
  1. Ebenhaeser Janse van Rensburg
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reinhardt A. Botha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bertram Haskins
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ebenhaeser Janse van Rensburg .

Editor information

Editors and Affiliations

  1. University of Plymouth, Plymouth, UK

    Nathan Clarke

  2. University of Nottingham, Nottingham, UK

    Steven Furnell

Rights and permissions

Reprints and permissions

Copyright information

© 2025 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

van Rensburg, E.J., Botha, R.A., Haskins, B. (2025). Research Agenda for Speaker Authentication. In: Clarke, N., Furnell, S. (eds) Human Aspects of Information Security and Assurance. HAISA 2024. IFIP Advances in Information and Communication Technology, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-031-72559-3_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-72559-3_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-72558-6

  • Online ISBN: 978-3-031-72559-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships

Search

Navigation