TY - GEN
T1 - Secure IoMT-CMS Communication
T2 - 30th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025
AU - Andreas, Andreou
AU - Mavromoustakis, Constandinos X.
AU - Batalla, Jordi Mongay
AU - Mastorakis, George
AU - Bourdena, Athina
AU - Markakis, Evangelos
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - The rapid adoption of Internet of Medical Things (IoMT) devices integrated with the proposed novel idea of Ceiling-Mounted Systems (CMS) significantly enhances healthcare data analytics and patient monitoring. However, this integration presents critical challenges related to data security, privacy, and efficient data transmission. Therefore, this study introduces an innovative cryptographic framework specifically designed to secure data exchange between IoMT devices and CMS infrastructures. The proposed system combines advanced encryption algorithms, circular matrix-based cryptographic methodologies, and deep reinforcement learning-based resource allocation to ensure data confidentiality, integrity, and timely transmission. Simulation results demonstrate that the proposed approach significantly outperforms traditional methods in reducing latency, optimizing energy consumption, and enhancing overall system security.
AB - The rapid adoption of Internet of Medical Things (IoMT) devices integrated with the proposed novel idea of Ceiling-Mounted Systems (CMS) significantly enhances healthcare data analytics and patient monitoring. However, this integration presents critical challenges related to data security, privacy, and efficient data transmission. Therefore, this study introduces an innovative cryptographic framework specifically designed to secure data exchange between IoMT devices and CMS infrastructures. The proposed system combines advanced encryption algorithms, circular matrix-based cryptographic methodologies, and deep reinforcement learning-based resource allocation to ensure data confidentiality, integrity, and timely transmission. Simulation results demonstrate that the proposed approach significantly outperforms traditional methods in reducing latency, optimizing energy consumption, and enhancing overall system security.
KW - Circular Matrices
KW - CMS
KW - Confidentiality
KW - Cryptography
KW - Data Security
KW - Deep Reinforcement Learning
KW - IoMT
UR - https://www.scopus.com/pages/publications/105026756972
U2 - 10.1109/CAMAD67323.2025.11229924
DO - 10.1109/CAMAD67323.2025.11229924
M3 - Conference contribution
AN - SCOPUS:105026756972
T3 - IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD
BT - 2025 IEEE 30th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 October 2025 through 16 October 2025
ER -
