Kanchana, S (2019) HISTOGRAM OF NEIGHBORHOOD TRIPARTITE AUTHENTICATION WITH FINGERPRINT-BASED BIOMETRICS FOR IOT SERVICES. International Journal of Computer Networks & Communications, 11 (5). pp. 21-37.

[thumbnail of 11519cnc02.pdf] Text
11519cnc02.pdf - Published Version
Download (412kB)

Abstract

Internet of Things (IoT) and services is an interesting topic with a wide range of potential applications like
smart home systems, health care, telemedicine, and intelligent transportation. Traditionally, key agreement
schemes have been evaluated to access IoT services which are highly susceptible to security. Recently,
Biometric-based authentication is also used to access IoT services and devices. They are involving a larger
amount of memory with increased running time and found to be computationally infeasible. To provide
robust authentication for IoT services, Histogram of Neighborhood Tripartite Authentication with
Fingerprint Biometrics (HNTA-FB) for IoT services is proposed in this paper. This proposed HNTA-FB
method uses binary patterns and a histogram of features to extract the region of interest. To reduce the
memory requirements while providing access to IoT services, Histogram of Neighborhood Binary Pattern
Pre-processing (HNBPP) model is proposed. The discriminative power of Neighbourhood Binary Pattern
Registration (NBPR) is integrated with the normalized sparse representation based on the histogram.
Additionally, this work presents a new Tripartite User Authentication model for fingerprint biometric
template matching process. When compared with different state-of-the-art methods, the proposed method
depicts significantly improved performance in terms of matching accuracy, computational overhead and
execution speed and is highly effective in delivering smart home services.

Item Type: Article
Uncontrolled Keywords: Binary Patterns, Fingerprint Biometrics, Histogram, Internet of Things, Neighborhood Tripartite Authentication.
Depositing User: Mr Team Mosys
Date Deposited: 02 Sep 2022 05:51
Last Modified: 02 Sep 2022 05:51
URI: http://ir.psgcas.ac.in/id/eprint/1516

Actions (login required)

View Item
View Item
Altmetric