Zobrazeno 1 - 10
of 1 622
pro vyhledávání: '"anti-spoofing"'
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-11 (2024)
Abstract Synthesis artifacts that span scales from small to large are important cues for spoofing detection. However, few spoofing detection models leverage artifacts across different scales together. In this paper, we propose a spoofing detection sy
Externí odkaz:
https://doaj.org/article/ea21ed20a568450594125710d075de29
Autor:
YUAN Weilin, ZHAO Weiwei, HU Zhenzhen, CAO Wei, HE Jun, DONG Shaojin, WANG Chengyuan, WANG Shengqing
Publikováno v:
智能科学与技术学报, Vol 6, Pp 284-300 (2024)
In the digital society of "open sharing of information and interconnection of everything", the information traces characterized with "massive, multi-source and explosive growth" in the internet provide rich "mineral deposits" for open-source intellig
Externí odkaz:
https://doaj.org/article/d3ccb739453e4edab8668be8db91e67e
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
The threat of spoofing interference has posed a severe challenge to the security application of Global Navigation Satellite System (GNSS). It is particularly urgent and critical to carry out in-depth defense research on spoofing interference. When co
Externí odkaz:
https://doaj.org/article/68664b6685cd44d4aad685d19aaed913
Autor:
Jing Zhang, Quanhao Guo, Xiangzhou Wang, Ruqian Hao, Xiaohui Du, Siying Tao, Juanxiu Liu, Lin Liu
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 4817-4833 (2024)
Abstract The significance of facial anti-spoofing algorithms in enhancing the security of facial recognition systems cannot be overstated. Current approaches aim to compensate for the model’s shortcomings in capturing spatial information by leverag
Externí odkaz:
https://doaj.org/article/6b99234a9a07486cbcd85d065ea949b3
Autor:
Padmashree G., Karunakar A. K.
Publikováno v:
Cogent Engineering, Vol 11, Iss 1 (2024)
Deep learning models have surpassed classic machine learning models in face anti-spoofing detection during the last decade. Most face-spoofing detection algorithms are biased toward a single presentation attack, failing to robustly detect multiple sp
Externí odkaz:
https://doaj.org/article/c545f03eee3048fcadc4ab7a37f3292a
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
IntroductionDespite advancements in face anti-spoofing technology, attackers continue to pose challenges with their evolving deceptive methods. This is primarily due to the increased complexity of their attacks, coupled with a diversity in presentati
Externí odkaz:
https://doaj.org/article/331a522e027841e1bc67b3315bbf4f88
Autor:
Md. Apu Hosen, Shahadat Hoshen Moz, Md. Mahamudul Hasan Khalid, Sk. Shalauddin Kabir, Dr. Syed Md. Galib
Publikováno v:
Радіоелектронні і комп'ютерні системи, Vol 0, Iss 2, Pp 119-128 (2023)
The subject matter of the article is the design of an attendance system based on face recognition with anti-spoofing, system alarm, and Email Automation to improve accuracy and efficiency, highlighting its potential to revolutionize traditional atten
Externí odkaz:
https://doaj.org/article/4f18494cd3c54c8780e6e668424136b1
Autor:
D. Zhuravlov, О. Polshakova
Publikováno v:
Adaptivni Sistemi Avtomatičnogo Upravlinnâ, Vol 1, Iss 42, Pp 108-114 (2023)
The object of the study is spoofing attacks on identification systems based on human face biometrics. The article provides an overview of the main types of spoofing attacks and features of their detection, as well as an overview of existing solutions
Externí odkaz:
https://doaj.org/article/c82b261aeeed4cdcb9f652db0d49e07d
Publikováno v:
IEEE Access, Vol 11, Pp 140443-140450 (2023)
The online hard example mining (OHEM) algorithm has been successfully applied for object detection in images. In this paper, we propose an innovative application of the OHEM algorithm for training synthetic speech spoofing detection models, which add
Externí odkaz:
https://doaj.org/article/d013094b9e994b7f9321df2802d17b28
Publikováno v:
IEEE Access, Vol 11, Pp 138986-139003 (2023)
Global Navigation Satellite System (GNSS) receivers are vulnerable to intentional spoofing attacks which can manipulate position, velocity, and time (PVT) measurements. Previous work has demonstrated that Time Synchronization Attacks (TSAs) can be de
Externí odkaz:
https://doaj.org/article/74ce82df72c34452a33d5bad1bd435aa