Wednesday, March 4, 2026

International Journal of Network Security & Its Applications (IJNSA)

International Journal of Network Security & Its Applications (IJNSA)
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)


OTN in the 5g Era: Transporting Massive Ip-Based Mobile Traffic
Joy Selasi Agbesi , Ohio University, USA

Abstract
Fifth-generation (5G) mobile networks impose unprecedented transport demands—high bandwidth, deterministic latency, and precise synchronization—driven by disaggregated RAN architectures (C-RAN/vRAN) and diverse service classes (eMBB, URLLC, mMTC) (Larsen et al., 2019; Zhang et al., 2020; Nakamura et al., 2018; Wijethilaka & Liyanage, 2021). This paper evaluates Optical Transport Network (OTN) as a foundation for 5G fronthaul and backhaul, focusing on protocol transparency, hierarchical grooming, latency determinism, operations/maintenance tooling, and carrier-grade protection (ITU-T, 2016; Cvijetic et al., 2017; Li et al., 2021). Using a synthesis of standards, deployments, and modeling, we show that OTN efficiently maps heterogeneous 5G traffic (e.g., CPRI/eCPRI, Ethernet), sustains microsecond-level latency and low jitter under load, and scales via ODUflex-based bandwidth granularity while meeting synchronization targets required by TDD and CoMP (Pizzinat et al., 2015; Velasco et al., 2014; ITU-T, 2020). Economic assessment indicates competitive lifecycle cost for high-capacity routes despite higher initial capex, especially where grooming efficiency and operational simplicity offset packet-only alternatives (Chen et al., 2019). We also discuss hybrid architectures pairing OTN with packet transport and SDN control to accelerate service provisioning and enable slice-aware automation (Raza et al., 2017; Taleb et al., 2017). The results provide an integrated framework and practical guidance for operators planning 5G transport, confirming OTN’s suitability for metro-scale fronthaul and aggregation backhaul today and its relevance as requirements evolve toward 6G (Zhang et al., 2020).

Keywords
Optical Transport Network, 5G networks, fronthaul, backhaul, network transport, bandwidth management, mobile networks, fiber optics, network architecture, telecommunications infrastructure





Monday, March 2, 2026

International Journal of Network Security & Its Applications (IJNSA) - ERA Indexed

#CallForPapers #CallForAbstracts #callforsubmissions #Papersubmission #deadline #online #article #articlesubmission #articlepublishing #papers #research #researchpaper #researchpublication #publication #Submission #submitnow #submissionsopen #SubmitYourPaper #SubmitYourAbstract #submityourwork



Welcome To IJNSA

International Journal of Network Security & Its Applications (IJNSA) - ERA Indexed
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)



Submission Deadline: March 07, 2026

Contact us:
Here's where you can reach us: ijnsa@aircconline.com (or) ijnsa@airccse.org (or) ijnsajournl@gmail.com


Sunday, March 1, 2026

International Journal of Network Security & Its Applications (IJNSA) - ERA Indexed, H Index - 52

#networksecurity #artificialintelligence #machinelearning #security #blockchain #technology #cybersecurity #cloud #fog #edge #crytography #protocols #datacenter #network #optimization #database #systemsecurity #spam #phishing #email #iot #internetsecurity #intrusion #detection #prevention #mobile #adhoc #sensor #p2p #networkmanagement #virtualmachines #vanet #socialnetwork #ddos #trust #privacy #wirelessnetwork #ubiquitouscomputing #virus #worms #trojan #hacking #ransomware #computer #cloudsecurity #malware #firewall #bigdata #informationsecurity #cloudcomputing #dataprotection #networking #cloudstorage #cybercrime #cyberattack #ethicalhacking #datasecurity #tech #itsecurity #internet #computerscience #server #dataprivacy



Submit Your Research Articles...!!!

Welcome To IJNSA

International Journal of Network Security & Its Applications (IJNSA) - ERA Indexed, H Index - 52
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)


Submission Deadline: March 07, 2026

Contact us:
Here's where you can reach us: ijnsa@aircconline.com (or) ijnsa@airccse.org (or) ijnsajournl@gmail.com


Friday, February 27, 2026

International Journal of Network Security & Its Applications (IJNSA)

#research #researchpaper #researchpublication #publication #Submission #submitnow #submissionsopen #SubmitYourPaper #SubmitYourAbstract #submityourwork #CallForPapers #CallForAbstracts #callforsubmissions #Papersubmission #deadline #online #article #articlesubmission #articlepublishing #papers



International Journal of Network Security & Its Applications (IJNSA)
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)


Citations 12192   h-index 52   i10-index 218

Contact us:
Here's where you can reach us: ijnsa@aircconline.com (or) ijnsa@airccse.org (or) ijnsajournl@gmail.com


Thursday, February 26, 2026

International Journal of Network Security & Its Applications (IJNSA) - ERA Indexed, H Index - 52

#intrusion #detection #prevention #mobile #adhoc #sensor #p2p #networkmanagement #virtualmachines #vanet #socialnetwork #ddos #trust #privacy #wirelessnetwork #ubiquitouscomputing #virus #worms #trojan #hacking #ransomware #computer #cloudsecurity #malware #firewall #bigdata #informationsecurity #cloudcomputing #dataprotection #networking #cloudstorage #cybercrime #cyberattack #ethicalhacking #datasecurity #tech #itsecurity #internet #computerscience #server #dataprivacy



Submit Your Research Articles...!!!

Welcome To IJNSA [March 2026, Volume 18, Number 2]

International Journal of Network Security & Its Applications (IJNSA) - ERA Indexed, H Index - 52
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)


Paper Submission
Authors are invited to submit papers for this journal through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.


Submission Deadline: February 28, 2026


For More Details, Please Visit: https://airccse.org/journal/ijnsa.html

Tuesday, February 24, 2026

International Journal of Network Security & Its Applications (IJNSA)

International Journal of Network Security & Its Applications (IJNSA)
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)


Machine Learning for Network Intrusion Detection in Usa Critical Infrastructure: Challenges and Opportunities
Joy Selasi Agbesi1, Abigail Nanayaa Otchill2, Raymond Horlalie Tay3 and Noah K. Bamfo4, 1Ohio University, USA, 2Foundation and Support, United States, 3College of Engineering Northeastern University, United States, 4Consulting Network Engineer, United States

Abstract
The convergence of information technology and operational technology in United States critical infrastructure has created unprecedented efficiency gains while simultaneously expanding attack surfaces vulnerable to sophisticated cyber threats. This paper examines the application of machine learning to network intrusion detection in critical infrastructure, with particular emphasis on smart cities and power grid implementations. Through comprehensive analysis of current threat landscapes, technical approaches, and operational constraints, the study identifies key challenges impeding the deployment of machine learning-based security solutions, including data scarcity, class imbalance, concept drift, and adversarial robustness concerns.
The analysis reveals that while machine learning offers promising capabilities for detecting anomalous patterns and previously unknown attack vectors beyond traditional signature-based systems, successful implementation requires addressing fundamental tensions between real-time operational requirements and computational complexity, between model explainability and detection accuracy, and between privacy preservation and effective security monitoring. The paper examines specific vulnerabilities in smart grid architectures, municipal systems, and IoT-enabled infrastructure, demonstrating how heterogeneous device ecosystems and legacy system integration compound security challenges.
Furthermore, the study synthesizes emerging opportunities including ensemble detection approaches, physics-informed machine learning, transfer learning techniques, federated learning, explainable artificial intelligence, and collaborative threat intelligence sharing mechanisms. It proposes a framework for crosssector collaboration and outlines standardized evaluation methodologies essential for validating machine learning security solutions in safety-critical environments. The findings indicate that realizing the full potential of machine learning for infrastructure protection requires coordinated efforts spanning technology development, workforce capacity building, regulatory framework evolution, and sustained information sharing across stakeholder communities. This work contributes to the growing body of knowledge on securing increasingly interconnected critical infrastructure systems upon which modern society fundamentally depends.

Keywords
Machine learning, intrusion detection, smart cities, smart grid, IoT security, anomaly detection, operational technology, cybersecurity, federated learning, explainable AI





International Journal of Network Security & Its Applications (IJNSA) - ERA Indexed

#systemsecurity #spam #phishing #email #iot #internetsecurity #intrusion #detection #prevention #mobile #adhoc #sensor #p2p #networkmanagement #virtualmachines #vanet #socialnetwork #ddos #trust #privacy #wirelessnetwork #ubiquitouscomputing #virus #worms #trojan #hacking #ransomware #computer #cloudsecurity #malware #firewall #bigdata #informationsecurity #cloudcomputing #dataprotection #networking #cloudstorage #cybercrime #cyberattack #ethicalhacking #datasecurity #tech #itsecurity #internet #computerscience #server #dataprivacy



Welcome To IJNSA

International Journal of Network Security & Its Applications (IJNSA) - ERA Indexed, H Index - 52
ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print)



Submission Deadline: February 28, 2026


International Journal of Network Security & Its Applications (IJNSA)

International Journal of Network Security & Its Applications (IJNSA) ISSN: 0974 - 9330 (Online); 0975 - 2307 (Print) Webpage URL: https:...