Asset Details
Do you wish to reserve the book?
Securing IoT Devices in Wireless Networks for Detection and Mitigation of MiTM and DDoS Attacks
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Securing IoT Devices in Wireless Networks for Detection and Mitigation of MiTM and DDoS Attacks
Do you wish to request the book?
Securing IoT Devices in Wireless Networks for Detection and Mitigation of MiTM and DDoS Attacks
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Securing IoT Devices in Wireless Networks for Detection and Mitigation of MiTM and DDoS Attacks
2025
Overview
This research aims to solve the security challenges faced by Internet of Things (IoT) devices in software defined networking (SDN) environments, with a particular focus on mitigating man-in-the-middle and distributed denial-of-service (DDoS) attacks. The proposed approach for DDOS involves generating a dataset from a data stream in the network, which is then trained and tested using machine learning algorithms such as KNN, SVM, RF, DT, and NB. The goal is to identify the algorithm that has the highest accuracy resulting from Training and testing of the target data, which is found to be Random Forest (RF), which we will use for forecasting and data analysis purposes, and Random Forest (RF) will be used in the proposed model to detect and mitigate Distributed Denial of Service (DDoS) attacks. Also to enhance security To protect against ARP spoofing attacks, lookup provides ARP with a mechanism to detect this type of attack. The mechanism includes the following steps: extracting packet information, learning MAC-to-Port assignments, and checking if the packet is an ARP request. If it is an ARP request, it will be stored Set IP-MAC. If mitigation is enabled and the packet is an ARP packet, the system will check for ARP spoofing. If ARP spoofing is detected, a stream entry is added to the switch the attacker attended. Otherwise, the packet is forwarded. If Mitigation is not enabled, the packet is simply forwarded. Search includes a stream entry management component that removes expired stream entries. If the specified flow entry expires, it is removed from the system to maintain efficiency and ensure security measures are up to date. By implementing this proposed model, IoT devices in SDN networks can be protected against DDoS attacks and ARP spoofing, thus enhancing the overall network security and reliability.
Publisher
مركز البحث وتطوير الموارد البشرية - رماح
Subject
