Accès libre

Secure transmission of wireless energy-carrying communication systems for the Internet of Things

À propos de cet article

Citez

Adhinugraha, K., et al., (2020). On Internet-of-Things (IoT) gateway coverage expansion. Future Generation Computer Systems, 107, p. 578-587. Search in Google Scholar

Morabito, R., et al., (2019). Reprint of : LEGIoT: A Lightweight Edge Gateway for the Internet of Things. Future Generation Computer Systems, 92, p. 1157-1171. Search in Google Scholar

Rahmani, A.M., et al., (2018). Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Future Generation Computer Systems, 78, p. 641-658. Search in Google Scholar

Jiang, W., (2022). Graph-based deep learning for communication networks: A survey. Computer Communications, 185, p. 40-54. Search in Google Scholar

Franek, L., et al., (2015). Multiwire Power Line Communication Model. IFAC-PapersOnLine, 48(4), p. 147-152. Search in Google Scholar

Zhang, S., et al., (2022). Standalone stretchable RF systems based on asymmetric 3D microstrip antennas with on-body wireless communication and energy harvesting. Nano Energy, 96, p. 107069. Search in Google Scholar

Hazzaa, F., et al., (2021). Security Scheme Enhancement for Voice over Wireless Networks. Journal of Information Security and Applications, 58, p. 102798. Search in Google Scholar

Xiao, X., et al., (2022). Battery-free wireless moisture sensor system for fruit monitoring. Results in Engineering, 14, p. 100420. Search in Google Scholar

Rugeles Uribe, J.D.J., E.P. Guillen and L.S. Cardoso, (2021). A technical review of wireless security for the internet of things: Software defined radio perspective. Journal of King Saud University - Computer and Information Sciences. Search in Google Scholar

Eder-Neuhauser, P., et al., (2017). Cyber attack models for smart grid environments. Sustainable Energy, Grids and Networks, 12, p. 10-29. Search in Google Scholar

Stellios, I., et al., (2018). A Survey of IoT-Enabled Cyberattacks: Assessing Attack Paths to Critical Infrastructures and Services. IEEE Communications Surveys & Tutorials, 20(4), p. 3453-3495. Search in Google Scholar

Fragkiadakis, A.G., E.Z. Tragos and I.G. Askoxylakis, (2013). A Survey on Security Threats and Detection Techniques in Cognitive Radio Networks. IEEE Communications Surveys & Tutorials, 15(1), p. 428-445. Search in Google Scholar

Yu, Y., W. Peng and J. Lu, (2022). Wireless network security game based on conditional privacy policy. Computer Communications, 184, p. 96-106. Search in Google Scholar

Huanan, Z., X. Suping and W. Jiannan, (2021). Security and application of wireless sensor network. Procedia Computer Science, 183, p. 486-492. Search in Google Scholar

Yu, J., X. Ye and H. Li, (2022). A high precision intrusion detection system for network security communication based on multi-scale convolutional neural network. Future Generation Computer Systems, 129, p. 399-406. Search in Google Scholar

Zhiqiang, L., et al., (2022). Intrusion detection in wireless sensor network using enhanced empirical based component analysis. Future Generation Computer Systems, 135, p. 181-193. Search in Google Scholar

Li, J., et al., (2022). Deep learning driven physical layer security for a simultaneously wireless information and power transfer network. Alexandria Engineering Journal, 61(9), p. 7429-7439. Search in Google Scholar

Hajar, M.S., M.O. Al-Kadri and H.K. Kalutarage, (2021). A survey on wireless body area networks: architecture, security challenges and research opportunities. Computers & Security, 104, p. 102211. Search in Google Scholar

O Mahony, G.D., et al., (2021). Developing novel low complexity models using received in-phase and quadrature-phase samples for interference detection and classification in Wireless Sensor Network and GPS edge devices. Ad Hoc Networks, 120, p. 102562. Search in Google Scholar

Gummineni, M. and T.R. Polipalli, (2021). Implementation of reconfigurable emergency wireless communication system through SDR relay. Materials Today: Proceedings. Search in Google Scholar

Narwal, B. and A.K. Mohapatra, (2021). A survey on security and authentication in wireless body area networks. Journal of Systems Architecture, 113, p. 101883. Search in Google Scholar

Zarpelão, B.B., et al., (2017). A survey of intrusion detection in Internet of Things. Journal of Network and Computer Applications, 84, p. 25-37. Search in Google Scholar

Tahsien, S.M., H. Karimipour and P. Spachos, (2020). Machine learning based solutions for security of Internet of Things (IoT): A survey. Journal of Network and Computer Applications, 161, p. 102630. Search in Google Scholar

Liu, X., et al., (2018). 5G-based green broadband communication system design with simultaneous wireless information and power transfer. Physical Communication, 28, p. 130-137. Search in Google Scholar

Hu, J., et al., (2022). Simultaneous wireless information and power transfer with fixed and adaptive modulation. Digital Communications and Networks. Search in Google Scholar

Yu, L., et al., (2022). Optimization of BP neural network model by chaotic krill herd algorithm. Alexandria Engineering Journal, 61(12), p. 9769-9777. Search in Google Scholar

Liu, Y., et al., (2022). Parameter optimization of L-joint of composite sandwich structure based on BPGA algorithm. Composite Structures, 289, p. 115508. Search in Google Scholar

Jian, J., et al., (2011). Inversion of Neural Network Rayleigh Wave Dispersion Based on LM Algorithm. Procedia Engineering, 15, p. 5126-5132. Search in Google Scholar

Liu, F., et al., (2017). Using scanning acoustic microscopy and LM-BP algorithm for defect inspection of micro solder bumps. Microelectronics Reliability, 79, p. 166-174. Search in Google Scholar

Moshkbar-Bakhshayesh, K., (2021). Identification of the appropriate architecture of multilayer feed-forward neural network for estimation of NPPs parameters using the GA in combination with the LM and the BR learning algorithms. Annals of Nuclear Energy, 156, p. 108222. Search in Google Scholar

Tao, J., et al., (2021). RBF neural network modeling approach using PCA based LM–GA optimization for coke furnace system. Applied Soft Computing, 111, p. 107691. Search in Google Scholar

eISSN:
2444-8656
Langue:
Anglais
Périodicité:
2 fois par an
Sujets de la revue:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics