Abstract
The Human-Centered Internet of Things (HC-IoT) is fast becoming a hotbed of security and privacy concerns. Two users can establish a common session key through a trusted server over an open communication channel using a three-party authenticated key agreement. Most of the early authenticated key agreement systems relied on pairing, hashing, or modular exponentiation processes that are computationally intensive and cost-prohibitive. In order to address this problem, this paper offers a new three-party authenticated key agreement technique based on fractional chaotic maps. The new scheme uses fractional chaotic maps and supports the dynamic sensing of HC-IoT devices in the network architecture without a password table. The projected security scheme utilized a hash function, which works well for the resource-limited HC-IoT architectures. Test results show that our new technique is resistant to password guessing attacks since it does not use a password. Furthermore, our approach provides users with comprehensive privacy protection, ensuring that a user forgery attack causes no harm. Finally, our new technique offers better security features than the techniques currently available in the literature.