Malicious Activity Detection Using Wireless Communication and Biometric Authentication in a Cyber-Physical System

Journal of Biometrics & Biostatistics

article

Charlie Moss¹ 

[1] Department of Biostatistics, Science and Technology of New York

关键词: Biometric technology;    SSOAE-BMA mode;   

DOI  :  10.37421/2155-6180.2022.13.130

来源: Hilaris Publisher

【 摘 要 】

Biometric technology has recently been extensively integrated intomobile devices to improve their security.Biometrics play a significant role instrengthening the detection of this privacy application as financial technology(FinTech) uses mobile applications and devices as promotional platforms. Thesalp swarm optimization with auto-encoder based biometric authentication(SSOAE-BMA) model for abnormal activity detection in Fintech bankingapplications based on wireless communication is presented in this paper.The SSOAE-BMA model's main goal is to use biometric matching to properlyauthenticate people.In the beginning, the stacked ResNet-50 model is used toderive feature vectors in the presented SSOAE-BMA model. Following that,the SSOAE-BMA model makes use of AE for biometric verification. The SocialSpider Optimization (SSO) .

【 授权许可】

Unknown