Editing Spoofing attack (section)

== Facial recognition spoofing ==
Facial recognition technology is widely employed in various areas, including immigration checks and phone security, as well as on popular platforms like [[Airbnb]] and [[Uber]] to verify individuals' identities. However, the increased usage has rendered the system more susceptible to attacks, given the widespread integration of facial recognition systems in society. Some online sources and tutorials detail methods for tricking facial recognition systems through practices known as face spoofing or presentation attacks, which can pose risks in terms of unauthorized access. To mitigate these dangers, measures such as [[liveness test|liveness check]]s (verifying blinking), [[deep learning]], and specialized cameras like 3D cameras have been introduced to prevent facial recognition spoofing. It is important to implement comprehensive security procedures like these to protect against face spoofing attempts and uphold the overall security and integrity of systems relying on facial recognition authentication.<ref>{{Cite book |last=Hadid |first=Abdenour |chapter=Face Biometrics Under Spoofing Attacks: Vulnerabilities, Countermeasures, Open Issues, and Research Directions |date=June 2014 |pages=113–118 |title=2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops |chapter-url=http://dx.doi.org/10.1109/cvprw.2014.22 |publisher=IEEE |doi=10.1109/cvprw.2014.22|isbn=978-1-4799-4308-1 |s2cid=9540938 }}</ref>