The article offers a comprehensive analysis of network coding, communications security, and coding theory, examining their applications and advancements. It evaluates the fundamental concepts and methodologies utilized in these fields while shedding light on current progress and potential future research directions. The implications of the study discussed in this article extend widely across the communication sector, with immediate practical applications across various disciplines. One of the key areas covered in the article is the development of novel error-correcting codes and coding algorithms, which contribute to enhancing communication reliability. Additionally, the integration of machine learning and artificial intelligence (AI) techniques into network communications security is explored, highlighting their potential to bolster safeguarding measures. Furthermore, the incorporation of security controls into connected devices and Internet of Things (IoT) networks is addressed, acknowledging the need to ensure security in these interconnected systems. To ensure the reliability and security of network communications and foster innovation and growth within the communication sector, the article concludes that coding theory and network communications security must continue to evolve and progress. By pushing the boundaries of these fields, researchers can address emerging challenges, improve existing systems, and pave the way for future advancements in communication technology.
D. Hurley and T. Hurley, “Coding theory: the unit-derived methodology,” Int. J. Inf. Coding Theory, vol. 5, no. 1, p. 55, 2018.
E. Goh, H. S. Venkataram, M. Hoffmann, M. D. Johnston, and B. Wilson, “Scheduling the NASA deep space network with deep reinforcement learning,” in 2021 IEEE Aerospace Conference (50100), 2021.
I. M. Boyarinov, “Self-checking circuits and decoding algorithms for binary hamming and BCH codes and Reed-Solomon codes over GF(2 m),” Probl. Inf. Transm., vol. 44, no. 2, pp. 99–111, 2008.
A. Khalid and P. Suksompong, “Application of maximum rank distance codes in designing of STBC-OFDM system for next-generation wireless communications,” Digit. Commun. Netw., 2023.
M. AlaaEldin, E. Alsusa, and K. G. Seddik, “IRS-assisted physical layer network coding over two-way relay fading channels,” IEEE Trans. Veh. Technol., vol. 71, no. 8, pp. 8424–8440, 2022.
王艺蒙 Wang Yimeng, 李蔚 Li Wei, 韩纪龙 Han Jilong, 姚海涛 Yao Haitao, 余少华 Yu Shaohua, and 杨奇 Yang Qi, “Upstream date transmission based on wavelet packet transform coding in passive optical network,” Zhongguo Jiguang (Chin. J. Lasers), vol. 41, no. 6, p. 0605001, 2014.
Z. Wang, S. S. Karande, H. R. Sadjadpour, and J. J. Garcia-Luna-Aceves, “On the multicast capacity of wireless ad hoc networks with network coding,” J. Commun. Netw., vol. 13, no. 5, pp. 525–535, 2011.
A. Wachter-Zeh and V. Sidorenko, “Rank metric convolutional codes for Random Linear Network Coding,” in 2012 International Symposium on Network Coding (NetCod), 2012.
M. Stasiak, M. Sobieraj, and P. Zwierzykowski, “Modeling of multi-service switching networks with multicast connections,” IEEE Access, vol. 10, pp. 5359–5377, 2022.
J. Park and D.-H. Cho, “Separated random linear network coding based on cooperative medium access control,” IEEE Netw. Lett., vol. 3, no. 2, pp. 66–69, 2021.
X. Wang, H. Li, M. Tong, K. Pan, and Q. Wu, “Network coded cooperative multicast in integrated terrestrial-satellite networks,” in 2019 IEEE Symposium on Computers and Communications (ISCC), 2019.
K. Zhang, L. Yin, and J. Lu, “Feedback-based adaptive network coded cooperation for wireless networks,” EURASIP J. Wirel. Commun. Netw., vol. 2011, no. 1, 2011.
S. Hong, K. Cheun, H. Lim, and S. Cho, “Performance of M-ary turbo coded synchronous FHSS multiple access networks with noncoherent MFSK under Rayleigh fading channels,” J. Commun. Netw., vol. 15, no. 6, pp. 601–605, 2013.
F. Aliyu, T. Sheltami, M. Deriche, and N. Nasser, “Human immune-based intrusion detection and prevention system for fog computing,” J. Netw. Syst. Manag., vol. 30, no. 1, 2022.
Anandakumar Haldorai, Shrinand Anandakumar, “An Design of Software Defined Networks and Possibilities of Network Attacks", vol.2, no.3, pp. 088-097, July 2022. doi: 10.53759/181X/JCNS202202012.
Acknowledgements
Authors thanks to Ministry of Science, ICT, Korea Institute for Advancement of Technology (KIAT) and Korea Government (MOTIE) for this research grant support.
Funding
This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ICAN (ICT Challenge and
Advanced Network of HRD) program (IITP-2023-2020-0-01825) and supervised by the IITP(Institute of Information &
Communications Technology Planning & Evaluation) and This research was partly supported by Institute for Information
& communications Technology Promotion(IITP) grant funded by the Korea Government(MSIT) and Korea Institute for
Advancement of Technology(KIAT) grant funded by the Korea Government(MOTIE) (P0008703, The Competency
Development Program for Industry Specialist)
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Rhee Jung Soo
Rhee Jung Soo
Department of Smart Convergence Security, Busan University of Foreign Studies, Busan,South Korea.
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Cite this article
Hye Jin Kim and Rhee Jung Soo, “A Comprehensive Study on the Advancements of Man and Machine in Network Security and Coding Theory, Journal of Machine and Computing, vol.3, no.3, pp. 227-237, July 2023. doi: 10.53759/7669/jmc202303021.