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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Mahmood Zaki Abdullah
Mustansiriyah University
Computer Science & IT Electrical & Electronics Engineering

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Design and implementation of a secured SDN system based on hybrid encrypted algorithms Samir Ghaly; Mahmood Zaki Abdullah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 4: August 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i4.18721

Abstract

Software defined network suggests centralizing network knowledge in one network portion by separating the routing (control plane) mechanism from the transmission network packet operation (data plane). The control plane is composed of one, two or more controllers which are considered as software-defined networking (SDN) network brain where the real intelligence is incorporated. The process of separating the control unit from the data unit led to a problem related to poor security of data sent in the network, so solutions to these problems had to be found. In this paper, address this problem by implementing robust algorithms to encrypt information, based on advanced encryption standard (AES), Rivest–Shamir–Adleman (RSA), and hybrid encryption algorithms to guarantee data protection and authenticity. The results showed that the hybrid coding method is better in terms of security and improved time (faster than RSA alone) by applying several scenarios in the SDN network to a set of encrypted files.
Prolonging WSNs lifetime in IoT applications based on consistent algorithm Mohammed Ali Tawfeeq; Mahmood Zaki Abdullah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 3: June 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i3.18355

Abstract

The rapid expansion in the use of IoT imposes the importance of developing its infrastructure. One of the most important components in IoT infrastructures is the wireless sensor networks. The development of these networks largely depends on how to extend their life. As one of the effective options adopted in this field is the use of cluster heads (CHs). This paper introduces an algorithm that efficiently determine the CHs by iteratively extracting an associative value for each node depending on two factors; node's residual energy, and geometrical distances between nodes and base station. In light of the extracted values, the nodes with the best associative values are elected as CHs based on adjustable threshold determined according to the network usage requirements. The algorithm has proven a significant increase in the lifetime of the network, as well as, it has proven its ability to maintain a high level of energy for long period of time. The proposed algorithm outperformed similar protocols like low energy adaptive clustering hierarchy (LEACH) and region based low energy adaptive clustering hierarchy (R-LEACH) by prolonging the network lifetime and increasing network stability, as well as enhances the throughput significantly.
Web and IoT-based hospital location determination with criteria weight analysis Abeer Hadi; Mahmood Zaki Abdullah
Bulletin of Electrical Engineering and Informatics Vol 11, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i1.3214

Abstract

The hospital location selection for COVID-19-infected patients is out to be one of the most critical decisions for healthcare sectors in high-case countries. In this study, optimal urban hospital location selection for COVID-19-infected patients has been done out of multiple alternative locations in city of Baghdad Iraq by introducing a web application system that can find the best site from alternatives by using MEREC and modified technique for order of preference by similarity to ideal solution (TOPSIS) algorithms. MEREC algorithm is utilized to obtain criteria weights and modified TOPSIS for ranking the alternatives. Four criteria are considered with eight alternatives sites. The proposed system has two-part, hardware part (embedded systems) designed by utilizing NEO-6M GPS receiver with ESP8266NodeMCU to obtain coordinate of regions and then, using the HTTP protocol to communicate to submit these data to database server. The second part is the web application developed by PHP, JavaScript, CSS, HTML, and MySQL used to allow the system admin to enter the locations of the alternatives with their criteria into the system to get the best urban hospital location for COVID-19-patients. The results showed effectiveness of overall suggested system and appropriateness of the modified TOPSIS method over the traditional TOPSIS method in ranking the alternative.
Distributed denial of service attacks detection for software defined networks based on evolutionary decision tree model Hasan Kamel; Mahmood Zaki Abdullah
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3835

Abstract

The software defined networks (SDN) system has modern techniques in networking, it separates the forwarding plane from the control plane and works to collect control functions in a central unit (controller), and this separation process leads to many advantages, such as cost reduction and programming ability. Concurrently, because of its centralized architecture, it is prone to a variety of attacks. Distributed denial of service (DDoS) attack has a significant impact on SDN, it is characterized by its ability to consume network resources as well as its ability to turn off the entire network. The work in this study aims to improve and increase the security and robustness of SDN systems against the attack or intrusion, by using a machine learning model to detect attack traffic and classify traffic of SDN as (attack or normal), and optimization algorithm (genetic algorithm) for improving the accuracy of the classification. After preparing and preprocessing the dataset, we used the genetic algorithm (GA) to optimize the hyperparameters of the decision tree (DT) model, and the proposed evolutionary decision tree (EDT) model was used to classify traffic into normal and attack traffic. The results indicate that the suggested model achieved a high classification accuracy of 99.46.
A new approach of extremely randomized trees for attacks detection in software defined network Hasan Kamel; Mahmood Zaki Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1613-1620

Abstract

Software defined networking (SDN) is the networking model which has completely changed the network through attempting to make devices of network programmable. SDN enables network engineers to manage networks more quickly, control networks from a centralized location, detect abnormal traffic, and distinguish link failures in efficient way. Aside from the flexibility introduced by SDN, also it is prone to attacks like distributed denial of service attacks (DDoS), that could bring the entire network to a halt. To reduce this threat, the paper introduces machine learning model to distinguish legitimate traffic from DDoS traffic. After preprocessing phase to dataset, the traffic is classified into one of the classes. We achieved an accuracy score of 99.95% by employing an optimized extremely randomized trees (ERT) classifier, as described in the paper. As a result, the goal of traffic flow classification using machine learning techniques was achieved.
Co-Authors Abeer Hadi Hasan Kamel Mohammed Ali Tawfeeq Samir Ghaly