EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 392 (2024) MATEC Web Conf., 392 (2024) 01121 References
Open Access
Issue
MATEC Web Conf.
Volume 392, 2024
International Conference on Multidisciplinary Research and Sustainable Development (ICMED 2024)
Article Number 01121
Number of page(s) 9
DOI https://doi.org/10.1051/matecconf/202439201121
Published online 18 March 2024
  1. Al Ameen .M, Liu. J and Kwak. K (2012), “Security and privacy issues in wireless sensor networks for healthcare applications”, Journal of Medical Systems, Vol.36, No. 1, pp. 93-101. [CrossRef] [Google Scholar]
  2. Zheng. G, Fang. G, Shankaran. R, Orgun.M. A, Zhou. J, Qiao. L and Saleem. K, (2016), “Multiple ECG fiducial points-based random binary sequence generation for securing wireless body area networks”, IEEE Journal of Biomedical and Health Informatics, Vol. 21, No. 3, pp. 655-663. [Google Scholar]
  3. Zhou. L and Chao .H.C (2011), “Multimedia traffic security architecture for the internet of things”, IEEE Network, Vol. 25, No. 3, pp. 35-40. [CrossRef] [Google Scholar]
  4. Ratha. N.K, Connell. J.H and Bolle. R.M (2001), “Enhancing security and privacy in biometrics-based authentication systems”, IBM systems Journal, Vol. 40, No. 3, pp. 614-634. [CrossRef] [Google Scholar]
  5. Ganesh, D., Kumar, T. P., & Kumar, M. S. (2021). OptimisedLevenshtein centroid crosslayer defence for multi‐hop cognitive radio networks. IET Communications, 15(2), 245-256. [CrossRef] [Google Scholar]
  6. Khan. A.A, Kumar. V and Ahmad .M (2019), “An elliptic curve cryptography based mutual authentication scheme for smart grid communications using biometric approach”, Journal of King Saud University-Computer and Information Sciences. [Google Scholar]
  7. Adamovic .S, Milosavljevic .M and Veinovic .M (2016), “Fuzzy commitment scheme for generation of cryptographic keys based on iris biometrics”, IET Biometrics, Vol. 6, No. 2, pp. 89-96. [Google Scholar]
  8. Algredo-Badillo. I, Feregrino-Uribe .C, Cumplido. R and Morales-Sandoval. M (2010), “Efficient hardware architecture for the AES-CCM protocol of the IEEE 802.11 i standard”, Computers & Electrical Engineering, Vol. 36, No. 3, pp. 565-577. [CrossRef] [Google Scholar]
  9. Ali. A and Khan. F.A (2013), “Energy-efficient cluster-based security mechanism for intra-WBAN and inter-WBAN communications for healthcare applications”, EURASIP Journal on Wireless Communications and Networking, Vol. 1, pp. 1-19. [Google Scholar]
  10. Ali, Shoukat et al. (2018), “Detection and prevention of Black Hole Attacks in IOT & WSN”, International Conference on Fog and Mobile Edge Computing, IEEE. [Google Scholar]
  11. Turukmane, A. V. ., Tangudu, N.. , Sreedhar, B.. , Ganesh, D.. , Reddy, P. S. S. ., &Batta, U.. (2023). An Effective Routing Algorithm for Load balancing in Unstructured Peerto-Peer Networks. International Journal of Intelligent Systems and Applications in Engineering, 12(7s), 87–97.. [Google Scholar]
  12. Zheng .G, Fang .G, Shankaran .R, Orgun .M.A, Zhou .J, Qiao .L and Saleem .K (2016), “Multiple ECG fiducial points-based random binary sequence generation for securing wireless body area networks”, IEEE Journal of Biomedical and Health Informatics, Vol. 21, No. 3, pp. 655-663. [Google Scholar]
  13. Yu, Weize and SelçukKose. (2017), “A lightweight masked AES implementation for securing IoT against CPA attacks”, IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 64, No. 11 pp. 2934-2944. [CrossRef] [Google Scholar]
  14. Yicheng, Chen, et al. (2008), “Energy-efficient and security-optimized AES hardware design for ubiquitous computing”, Journal of Systems Engineering and Electronics, Vol. 19.4, pp. 652-658. [CrossRef] [Google Scholar]
  15. Wu .Z, Tian .L, Li .P, et al. (2018), “Generating stable biometric keys for flexible cloud computing authentication using finger vein”, Information Sciences, Vol. 433, pp. 431-447. [CrossRef] [Google Scholar]
  16. Verma .G, Liao .M, Lu .D et al. (2019), “An optical asymmetric encryption scheme with biometric keys”, Optics and Lasers in Engineering, Vol. 116, pp. 32-40. [CrossRef] [Google Scholar]
  17. D. Ganesh et al., “Implementation of Novel Machine Learning Methods for Analysis and Detection of Fake Reviews in Social Media,” 2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS), Erode, India, 2023, pp. 243-250, doi: 10.1109/ICSCDS56580.2023.10104856 [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.