A Hybrid AES with a Chaotic Map-Based Biometric Authentication Framework for IoT and Industry 4.0

Abstract

The Internet of Things (IoT) is being applied in multiple domains, including smart homes and energy management. This work aims to tighten security in IoTs using fingerprint authentications and avoid unauthorized access to systems for safeguarding user privacy. Captured fingerprints can jeopardize the security and privacy of personal information. To solve privacy- and security-related problems in IoT-based environments, Biometric Authentication Frameworks (BAFs) are proposed to enable authentications in IoTs coupled with fingerprint authentications on edge consumer devices and to ensure biometric security in transmissions and databases. The Honeywell Advanced Encryption Security-Cryptography Measure (HAES-CM) scheme combined with Hybrid Advanced Encryption Standards with Chaotic Map Encryptions is proposed. BAFs enable private and secure communications between Industry 4.0’s edge devices and IoT. This work’s suggested scheme’s evaluations with other encryption methods reveal that the suggested HAES-CM encryption strategy outperforms others in terms of processing speeds.

Keywords

• Internet of Things
• security
• fingerprint authentication
• privacy
• Biometric Authentication Framework
• biometric data