  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.
