Securing Hybrid Wireless Body Area Networks (HyWBAN): Advancements in Semantic Communications and Jamming Techniques

TL;DR

This paper introduces a dual-layer security approach for HyWBANs using semantic communications and jamming receivers, improving security and reducing energy consumption in biomedical wireless networks.

Contribution

It presents a novel combination of semantic communication and jamming techniques for enhanced security in HyWBANs, with deep learning-based cryptographic key generation.

Findings

Significant energy savings over traditional cryptography.

Effective protection against cyber-attacks in biomedical communications.

Validated through laboratory measurements and deep learning models.

Abstract

This paper explores novel strategies to strengthen the security of Hybrid Wireless Body Area Networks (HyWBANs), essential in smart healthcare and Internet of Things (IoT) applications. Recognizing the vulnerability of HyWBAN to sophisticated cyber-attacks, we propose an innovative combination of semantic communications and jamming receivers. This dual-layered security mechanism protects against unauthorized access and data breaches, particularly in scenarios involving in-body to on-body communication channels. We conduct comprehensive laboratory measurements to understand hybrid (radio and optical) communication propagation through biological tissues and utilize these insights to refine a dataset for training a Deep Learning (DL) model. These models, in turn, generate semantic concepts linked to cryptographic keys for enhanced data confidentiality and integrity using a jamming receiver. The proposed model demonstrates a significant reduction in energy consumption compared to traditional cryptographic methods, like Elliptic Curve Diffie-Hellman (ECDH), especially when supplemented with jamming. Our approach addresses the primary security concerns and sets the baseline for future secure biomedical communication systems advancements.