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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Ahmed A. Hashim
University of Information Technology and Communications

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Design of dual band slotted reconfigurable antenna using electronic switching circuit Mustafa M. Al-Saeedi; Ahmed A. Hashim; Omer Al-Bayati; Ali Salim Rasheed; Rasool Hasan Finjan
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 1: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i1.pp386-393

Abstract

This paper proposes a dual band reconfigurable microstrip slotted antenna for supporting the wireless local area network (WLAN) and worldwide interoperability for microwave access (WiMAX) applications, providing coverage where both directive and omni-directive radiations are needed. The design consists of a feedline, a ground plane with two slots and two gaps between them to provide the switching capability and a 1.6 mm thick flame retardant 4 (FR4) substrate (dielectric constant Ɛ=4.3, loss tangent δ=0.019), modeling an antenna size of 30x35x1.6 mm3. The EM simulation, which was carried out using the connected speech test (CST) studio suite 2017, generated dual wide bands of 40% (2-3 GHz) with -55 dB of S11 and 24% (5.2-6.6 GHz) higher than its predecessors with lower complexity and -60 dB of S11 in addition to the radiation pattern versatility while maintaining lower power consumption. Moreover, the antenna produced omnidirectional radiation patterns with over than 40% bandwith at 2.4 GHz and directional radiation patterns with 24% bandwith at the 5.8 GHz band. Furthermore, a comprehensive review of previously proposed designs has also been made and compared with current work.
Development of a new system to detect denial of service attack using machine learning classification Mohammad M. Rasheed; Alaa K. Faieq; Ahmed A. Hashim
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp1068-1072

Abstract

Denial of service (DoS) attack is among the most significant types of attacks in cyber security. The objective of this research is to introduce a new algorithm to distinguish normal service requests from the denial of service attacks. Our proposed approach can detect the denial of service attacks by the analysis of the packets sent from the client to the server, which depend on machine learning. Our algorithm collects different datasets of benign network traffic and different types of denial of service attacks, such as DDoS, DoS Hulk, DoS GoldenEye, DoS Slowhttptest and DoS Slowloris, that were used for training. Moreover, our algorithm monitors the network every specific time to find denial of service attack. Our results show that the algorithm can detect the benign cases and distinguish the types of denial of service attack. Furthermore, the results could achieve 99 percentage of correct classification of all selected cases.
Co-Authors Alaa K. Faieq Ali Salim Rasheed Mohammad M. Rasheed Mustafa M. Al-Saeedi Omer Al-Bayati Rasool Hasan Finjan