Article Per Year (5 Year)
p-Index From 2021 - 2026
1.006
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Okokpujie, Kennedy
Unknown Affiliation
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : International Journal of Electrical and Computer Engineering

 1 
Hybridization of the Q-learning and honey bee foraging algorithms for load balancing in cloud environments Adewale, Adeyinka Ajao; Obiazi, Oghorchukwuyem; Okokpujie, Kennedy; Koto, Omiloli
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4602-4615

Abstract

Load balancing (LB) is very critical in cloud computing because it keeps nodes from being overloading while others are idle or underutilized. Maintaining the quality of service (QoS) characteristics like response time, throughput, cost, makespan, resource utilization, and runtime is difficult in cloud computing due to load balancing. A robust resource allocation strategy contributes to the end user receiving high-quality cloud computing services. An effective LB strategy should improve and deliver required user satisfaction by efficiently using the resources of virtual machines (VM). The Q-learning method and the honey bee foraging load balancing algorithm were combined in this study. This hybrid combination of a load balancing algorithm and a machine learning method has reduced the runtime of load balancing activities and makespan, and increased task throughput in a cloud computing environment thereby enhancing routing activities. It achieved this by continuously tracking the usage histories of the VMs and altering the usage matrix to send jobs to the VMs with the best usage histories.
Implementation of a network intrusion detection system for man-in-the-middle attacks Okokpujie, Kennedy; Abdulateef-Adoga, William A.; Owivri, Oghenetega C.; Ijeh, Adaora P.; Okokpujie, Imhade P.; Awomoy, Morayo E.
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp6027-6042

Abstract

Intrusion detection systems (IDS) are critical tools designed to detect and prevent unauthorized access and potential network threats. While IDS is well-established in traditional wired networks, deploying them in wireless environments presents distinct challenges, including limited computational resources and complex infrastructure configurations. Packet sniffing and man-in-the-middle (MitM) attacks also pose significant threats, potentially compromising sensitive data and disrupting communication. Traditional security measures like firewalls may not be sufficient to detect these sophisticated attacks. This paper implements a network intrusion detection system that monitors a computer network to detect Address Resolution Protocol spoofing attacks in real-time. The system comprises three host machines forming the network. Using Kali Linux, a bash script is deployed to monitor the network for signs of address resolution protocol (ARP) poisoning. An email alert system is integrated into the bash script, running in the background as a service for the network administrator. Various ARP spoofing attack scenarios are performed on the network to evaluate the efficiency of the network IDS. Results indicate that deploying IDS as a background service ensures continuous protection against ARP spoofing and poisoning. This is crucial in dynamic network environments where threats may arise unexpectedly.
Co-Authors Abdulateef-Adoga, William A. Adaora, Ijeh Princess Adewale, Adeyinka Ajao Agamah, Alvin K. Anointing, Tamunowunari-Tasker Awomoy, Morayo E. Awomoyi, Morayo E. Awomoyi, Morayo Emitha Daramola, Samuel Daramola, Samuel Adebayo Ijeh, Adaora P. Ijeh, Adaora Princess Koto, Omiloli Mommoh, Joshua Sokowonci Obiazi, Oghorchukwuyem Ogundele, Mary Oluwafeyisayo Oguntuyo, Oluwadamilola Okokpujie, Imhade P. Okokpujie, Imhade Princess Olusanya, Olamide Omolara, Olusanya Olamide Orimogunje, Abidemi Owivri, Oghenetega Owivri, Oghenetega C. Tolulope, Adekoya