Security-Level Improvement of IoT-Based Systems Using Biometric Features

Abstract

The Internet of Things (IoT) is reported as a main research topic in the current decade. It will be possible to connect smart devices to each other using IoT, a platform such as the Internet. However, the expansion and intrusion of such a large network raises some new security issues and risks related to the disclosure of user confidential information where these devices are subject to hacker threats and intrusions. Traditional security systems were password based. In this paper, after reviewing the actions taken in this regard, the improvement level of biometric security compared with traditional password-based methods will be proven in section three using the Markov model. By considering the results of the evaluation, the probability of occurrence of security problems is decreased by 90.71% by applying biometric features. Then, multi-layer security architecture with biometric features and coding systems is suggested to increase security. In the first layer, the fingerprint recognition algorithm is dependent on the module, and the U.are.U 5100 module provides more security than others. In the second layer, the Hash mechanism of the MD5 algorithm is, on average, 63.21% more efficient. By determining the properties of the first two architectural layers and ultimately for the IoT application layer, empirical methods and hardware platforms for the Internet of things are used. Concerning the simulation results, the suggested mechanism enhances the system security by 120.38% on average, which is 106.23, 110.45, and 144.46% of relative improvement compared with IoT sensors, controller layer mechanisms, and application layer mechanisms, respectively.

An AI-Driven Hybrid Framework for Intrusion Detection in IoT-Enabled E-Health

“…e extensive connectivity and continuous sharing of data of these devices make them a prime target of di erent threat actors that can execute anomalous activities against them [6]. e exploit's motivations are to obtain important information, steal money, and damage the system's resources [7][8][9].…”

“…While providing significant benefits, the pervasive and open nature of the IoMT ecosystem makes it a possible target for various emerging cyber threats and attacks [ 2 – 5 ]. The extensive connectivity and continuous sharing of data of these devices make them a prime target of different threat actors that can execute anomalous activities against them [ 6 ]. The exploit's motivations are to obtain important information, steal money, and damage the system's resources [ 7 – 9 ].…”

IoT-Based Biometric Recognition Systems in Education for Identity Verification Services: Quality Assessment Approach

“…Biometric authentications are popular, more reliable, and user-friendly than conventional methods. The previous research has discussed IoT issues and challenges regarding biometric security and application, including where biometrics can be integrated into IoT infrastructure [26], [51], [57].…”