Authors :
Umang H Patel; Krish Gera
Volume/Issue :
Volume 9 - 2024, Issue 6 - June
Google Scholar :
https://tinyurl.com/2hzmnssb
Scribd :
https://tinyurl.com/mwvypx3h
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24JUN1510
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
A new age of accuracy and efficiency,
especially in face recognition and other biometric
technologies, has been brought about in recent years by
the integration of artificial intelligence (AI) into
biometric security systems. The discussion extends to the
security implications of AI-enhanced biometric systems,
including their susceptibility to threats such as spoofing
and adversarial attacks. We analyze the vulnerabilities
these systems face and propose advanced algorithmic
solutions to fortify them against such risks. Moreover,
this paper addresses the ethical and privacy concerns
surrounding the widespread use of biometric data,
emphasizing the need for stringent data protection
measures and regulatory compliance. Additionally, the
research investigates AI's significant contributions to
genetic engineering, particularly through advancements
in CRISPR [1] technology. By integrating AI, the
precision of gene editing can be significantly improved,
potentially revolutionizing personalized medicine and
genetic therapies. This extensive research intends to shed
light on the revolutionary potential of artificial
intelligence (AI) in genetic engineering and biometric
security, emphasizing both the exciting developments
and the difficult obstacles still to be overcome. Through
this research, readers will get a clearer knowledge of
how artificial intelligence (AI) is altering biotechnology
and security, opening the door for discoveries that might
have a significant influence on healthcare and other
fields.
Keywords :
AI, Biometric Security, Facial Recognition, Machine Learning, Privacy Concerns.
References :
- Garvie, C., Bedoya, A. M., & Frankle, J. (2016). "The Perpetual Line-Up: Unregulated Police Face Recognition in America." Georgetown Law Center on Privacy & Technology https://www. perpetuallineup.org/
- HSBC Press Release. (2018). "HSBC Introduces Fingerprint and Voice ID Security." Retrieved from https://www.hsbc. com/news-and-media
- Amazon Developer Blog. (2019). "Alexa Voice Profiles: Recognize Users and Personalize Experiences." https://developer.amazon.com/blogs/ alexa/post/9d45b5e3-2398-4ad7-8887-7684e63b0039 /alexa-voice-profiles-recognize-users-and-personalizeb-experi ences
- Parkhi, O. M., Vedaldi, A., & Zisserman, A. (2015). "Deep face recognition." British Machine Vision Conference. Retrieved from https://www.robots.ox. ac.uk/~vgg/publications/2015/Parkhi15/
- Graves, A., Mohamed, A.-r., & Hinton, G. (2013). "Speech recognition with deep recurrent neural networks." IEEE International Conference on Acoustics, Speech. https://ieeexplore.ieee.org/ document/6638947
- M. O. Ozcan, F. Odaci and I. Ari, "Remote Debugging for Containerized Applications in Edge Computing Environments," 2019 IEEE International Conference on Edge Computing (EDGE), Milan, Italy, 2019, pp. 30-32, doi: 10.1109/EDGE.2019. 00021.
- Rattani, A., Kisku, D. R., Bicego, M., & Tistarelli, M. (2010). "Feature Level Fusion of Face and Fingerprint Biometrics." IEEE International Conference on Biometrics: Theory Applications and Systems. https://ieeexplore.ieee.org/document/ 5634524
A new age of accuracy and efficiency,
especially in face recognition and other biometric
technologies, has been brought about in recent years by
the integration of artificial intelligence (AI) into
biometric security systems. The discussion extends to the
security implications of AI-enhanced biometric systems,
including their susceptibility to threats such as spoofing
and adversarial attacks. We analyze the vulnerabilities
these systems face and propose advanced algorithmic
solutions to fortify them against such risks. Moreover,
this paper addresses the ethical and privacy concerns
surrounding the widespread use of biometric data,
emphasizing the need for stringent data protection
measures and regulatory compliance. Additionally, the
research investigates AI's significant contributions to
genetic engineering, particularly through advancements
in CRISPR [1] technology. By integrating AI, the
precision of gene editing can be significantly improved,
potentially revolutionizing personalized medicine and
genetic therapies. This extensive research intends to shed
light on the revolutionary potential of artificial
intelligence (AI) in genetic engineering and biometric
security, emphasizing both the exciting developments
and the difficult obstacles still to be overcome. Through
this research, readers will get a clearer knowledge of
how artificial intelligence (AI) is altering biotechnology
and security, opening the door for discoveries that might
have a significant influence on healthcare and other
fields.
Keywords :
AI, Biometric Security, Facial Recognition, Machine Learning, Privacy Concerns.