Comparison of cloud and edge computing based face recognition for security enhancement

Chaturvedi, Rekha; Gupta, Puja; Pandey, Ramesh Chand; Rathore, Neeraj Kumar; Sharma, Abhay; Dadheech, Pankaj; Sharma, Rahul

doi:10.47974/JDMSC-2370

Open Access Research Article

Comparison of cloud and edge computing based face recognition for security enhancement

Rekha Chaturvedirekha.chaturvedi@jaipur.manipal.eduDepartment of Data Science and Engineering Manipal University Jaipur Jaipur, Rajasthan, 303007, IndiaView full profile → , Puja Guptapooja1porwal@gmail.comDepartment of Information Technology Shri G.S. Institute of Technology & ScienceIndore, Madhya Pradesh, 452003, IndiaView full profile → , Ramesh Chand Pandeyrcpandey@recabn.ac.inDepartment of Information Technology Rajkiya Engineering College Ambedkar Nagar Ambedkar Nagar, Uttar Pradesh, 224122, IndiaView full profile → , Neeraj Kumar Rathoreneerajrathore37@gmail.comDepartment of Computer Science Indira Gandhi National Tribal UniversityAmarkantak, Madhya Pradesh, 484887, IndiaView full profile → , ^*Abhay SharmaCorresponding authorabhay.sharma@jaipur.manipal.eduDepartment of IoT & Intelligent System Manipal University JaipurJaipur, Rajasthan, 303007, IndiaView full profile → , Pankaj Dadheechpankajdadheech777@gmail.comDepartment of Computer Science & Engineering Swami Keshvanand Institute of Technology, Management & GramothanDepartment of Computer Science & Engineering Swami Keshvanand Institute of Technology, Management & GramothanJaipur, Rajasthan, 302017, IndiaView full profile → , Rahul Sharmarahul.sharma@jaipur.manipal.eduDepartment of Computer and Communication Engineering Manipal University JaipurJaipur, Rajasthan, 303007, IndiaView full profile →

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pp. 1945–1955Vol. 28Issue 5-BAugust 2025DOI: 10.47974/JDMSC-2370 Crossmark XML

Received:: 07 Aug 2024
Published Online:: 30 Aug 2025
Article type:: Research Article
Language:: EN
Article no.:: JDMSC-2370
Pages:: 1945–1955

Abstract

The implementation of novel intelligent applications has resulted in security enhancement in the way information is managed. The processing, storing, and functional aspects of computer systems have all been impacted by this revolution. Cloud computing has become a widely adopted and extensively utilized concept. Unfortunately, there are still some obstacles that prevent the widespread use of cloud computing. Edge computing refers to a decentralized kind of computing that allows the processing of data at its source, extending beyond traditional centralized systems. This research study introduces an innovative and efficient approach for identifying human faces for access control and security monitoring using sophisticated deep-learning algorithms. The proposed approach employs the results of two models trained using VGG face and ResNet architectures, respectively. Integrating these models with the deep face model enhances the accuracy and reliability of facial recognition. The process involves extracting distinguishing characteristics from facial photos using pre-trained VGG face and ResNet models. Subsequently, the deep face model is used to merge the characteristics, hence permitting improved portrayal and recognition of facial features. The proposed methodology has been verified by empirical evaluations, which have shown its effectiveness in improving precision and robustness in tasks associated with human facial recognition. The work significantly enhances the advancement of deep learning techniques in the field of face recognition applications for security enhancement.

Keywords

Deep learning Transfer learning Convolutional neural network (CNN)Cryptography and security Smart surveillance

Subject Classifications

68M25

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