RETRACTED: Biometric authentication integrated with wireless communication malicious activity detection in a cyber physical system-based Fintech banking (Retracted Article)

被引:0
作者
Alorfi, Almuhannad Sulaiman [1 ]
Yonbawi, Saud [2 ]
Alahmari, Sultan [3 ]
Bozorboevich, Abdullaev Abror [4 ]
Arumugam, Mahendran [5 ]
Huy, Pham Quang [6 ]
机构
[1] King Abdulaziz Univ, Fac Comp & Informat Technol, Dept Informat Syst, City Rabigh, Saudi Arabia
[2] Univ Jeddah, Coll Comp Sci & Engn, Dept Software Engn, Jeddah, Saudi Arabia
[3] King Abdul Aziz City Sci & Technol, Riyadh, Saudi Arabia
[4] Tashkent Inst Finance, Dept Acconting Econ Anal & Audit, Tashkent, Uzbekistan
[5] Saveetha Inst Med & Tech Sci, Saveetha Dent Coll, Ctr Transdisciplinary Res, Chennai, India
[6] Univ Econ Ho Chi Minh City UEH, Ho Chi Minh City, Vietnam
来源
OPTIK | 2023年 / 272卷
关键词
Biometric authentication; Cyber physical system; Deep learning; Wireless communication; Fintech banking; Malicious activities;
D O I
10.1016/j.ijleo.2022.170294
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Recently, biometric technology has been extensively embedded in mobile devices to enhance security of mobile devices. With rise of financial technology (FinTech) that employs mobile applications as well as devices as promotional platforms, biometrics has a significant role in strengthening the detection of this privacy application. This manuscript offers the design of salp swarm optimization with auto-encoder based biometric authentication (SSOAE-BMA) model for the recognition of abnormal activities in the Fintech banking applications based on wireless communication. The major aim of the SSOAE-BMA model lies in the proper authentication of persons via biometric matching process. Initially, the presented SSOAE-BMA model makes use of stacked ResNet-50 model for deriving feature vectors. Next, the SSOAE-BMA model utilizes AE for biometric verification and the performance of the AE model is adjusted using the Social Spider Optimization (SSO) Algorithm which in turn enhances the recognition outcomes. To demonstrate the improved performance of SSOAE-BMA model, a series of simulations were carried out. The experimental outcomes signified the enhancements of the SSOAE-BMA model over existing models.
引用
收藏
页数:11
相关论文
共 19 条
  • [1] Edge-centric multimodal authentication system using encrypted biometric templates
    Ali, Zulfiqar
    Hossain, M. Shamim
    Muhammad, Ghulam
    Ullah, Ihsan
    Abachi, Hamid
    Alamri, Atif
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 85 : 76 - 87
  • [2] Autoencoder-based deep metric learning for network intrusion detection
    Andresini, Giuseppina
    Appice, Annalisa
    Malerba, Donato
    [J]. INFORMATION SCIENCES, 2021, 569 (569) : 706 - 727
  • [3] Bandara O. K. K., 2019, MODEL ASSESSING MATU, P1141
  • [4] Correcting design flaws: An improved and cloud assisted key agreement scheme in cyber physical systems
    Chaudhry, Shehzad Ashraf
    Shon, Taeshik
    Al-Turjman, Fadi
    Alsharif, Mohammed H.
    [J]. COMPUTER COMMUNICATIONS, 2020, 153 : 527 - 537
  • [5] Chen F., 2021, Secur Commun Netw, V2021
  • [6] Survey on automated symbolic verification and its application for synthesising cyber-physical systems
    Cordeiro, Lucas C.
    de Lima Filho, Eddie B.
    Bessa, Iury V.
    [J]. IET CYBER-PHYSICAL SYSTEMS: THEORY & APPLICATIONS, 2020, 5 (01) : 1 - 24
  • [7] Neuromanagement decision making in facial recognition biometric authentication as a mobile payment technology in retail, restaurant, and hotel business models
    Dijmarescu, Irina
    Iatagan, Mariana
    Hurloiu, Iulian
    Geamanu, Marinela
    Rusescu, Ciprian
    Dijmarescu, Adrian
    [J]. OECONOMIA COPERNICANA, 2022, 13 (01) : 225 - 250
  • [8] Ibrokhimov S, 2019, INT CONF ADV COMMUN, P279, DOI [10.23919/ICACT.2019.8701960, 10.23919/icact.2019.8701960]
  • [9] Jama A.Y., 2018, P SCI INF C, P1021
  • [10] Diamond Accountability Model for Blockchain-enabled Cyber-Physical Systems
    Kanak, Alper
    Ugur, Niyazi
    Ergun, Salih
    [J]. PROCEEDINGS OF THE 2020 IEEE INTERNATIONAL CONFERENCE ON HUMAN-MACHINE SYSTEMS (ICHMS), 2020, : 155 - 159