Physical Visitor Access Control and Authentication Using Blockchain, Smart Contracts and Internet of Things

Stock, Frederick; Peker, Yeşem Kurt; Pérez, Alfredo; Hearst, Jarel

doi:10.3390/cryptography6040065

Cited by 3 publications

(1 citation statement)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A large number of objects with a mass stay of people, such as enterprises, office centers, public institutions, educational organizations require an physical access control system (PACS) [1,2]. This is important both for the safety of people, the safety of property, and for controlling working hours, maintaining databases of personnel and visitors.…”

Section: Introductionmentioning

confidence: 99%

Development of software and hardware complex for control and access management based on face recognition algorithms and neural networks

Rada

Тимофеев

Kon’kov

et al. 2023

International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023)

View full text Add to dashboard Cite

The purpose of the study is to develop and test a software and hardware complex for access control and management using face recognition algorithms and neural network technology. A software and hardware complex was used, including turnstiles with swing doors, single-board mini-computers on each turnstile, webcams, sensors, an integrated graphics processor, as well as a software development kit for developers. Siamese neural network “FaceNet” was used for face recognition. When training a neural network, each face image is associated with a feature vector lying on the N-dimensional hyposphere. The study developed and tested photo pre-processing algorithms (to exclude irrelevant images), as well as the biometric PACS algorithm. Approbation of the developed hardware and software system on the campus of the Kemerovo State University (Kemerovo, Kemerovo region – Kuzbass, Russia) showed that the average frame processing speed is high (0.076 seconds per frame), which ensures a fairly fast pass of people. This result is achieved on the basis of the image pre-processing algorithm. During the first test of the software and hardware complex, it was found that 60% of the frames are excluded from the analysis by the neural network. Errors of the first kind (passing people who do not have the right to pass) were observed in 4% of cases. After setting up and calibrating the software and hardware complex, the proportion of such errors decreased to 0.4% of the total number of frames processed by the neural network.

show abstract

Section: Introductionmentioning

confidence: 99%

Development of software and hardware complex for control and access management based on face recognition algorithms and neural networks

Rada

Тимофеев

Kon’kov

et al. 2023

International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023)

View full text Add to dashboard Cite

show abstract

Efficient Authentication System Based On Blockchain Using eID card

Liu,

Omote

2023

2023 IEEE International Conference on Blockchain (Blockchain)

View full text Add to dashboard Cite

Cloud-Based Access Control Including Time and Location

Al Lail,

Moncivais,

Benton

et al. 2024

Electronics

View full text Add to dashboard Cite

Location-based services (LBS) offer various functionalities, but ensuring secure access to sensitive user data remains a challenge. Traditional access control methods often need more detail to enforce location-specific restrictions. This paper proposes a new approach that utilizes the Generalized Spatio-Temporal Role-Based Access Control Model (GSTRBAC) within the context of LBS. GSTRBAC grants access based on user credentials, authorized locations, and access times, providing a detailed approach to securing LBS data. We introduce an optimized cloud-based GSTRBAC implementation suitable for deployment in modern LBS architectures. The system uses two secure communication protocols tailored to different security requirements. This allows for efficient communication for less-sensitive data while offering robust protection for highly sensitive information. Additionally, a proof-of-concept mobile application demonstrates the system’s functionality and efficiency within an LBS environment. Our evaluation confirms the effectiveness of the cloud-based GSTRBAC implementation in enforcing location-specific access control while maintaining resource and time efficiency.

show abstract

Physical Visitor Access Control and Authentication Using Blockchain, Smart Contracts and Internet of Things

Cited by 3 publications

References 37 publications

Development of software and hardware complex for control and access management based on face recognition algorithms and neural networks

Development of software and hardware complex for control and access management based on face recognition algorithms and neural networks

Efficient Authentication System Based On Blockchain Using eID card

Cloud-Based Access Control Including Time and Location

Contact Info

Product

Resources

About