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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Sara Chadli
Mohammed First University

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Modeling the impact of jamming attacks in the internet of things Imane Kerrakchou; Sara Chadli; Yassine Ayachi; Mohammed Saber
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1206-1215

Abstract

Security is a key requirement in the context of the Internet of Things. The IoT is connecting many objects together via wireless and wired connections with the goal of allowing ubiquitous interaction, where all components may communicate with others without constraints. The wireless sensor network is one of the most essential elements of IoT concepts. Because of their unattended and radio-shared nature for communication, security is becoming an important issue. Wireless sensor nodes are susceptible to different types of attacks. Such attacks can be carried out in several various ways. One of the most commonly utilized methods is Jamming. However, there are also some other attack types that we need to be aware of, such as Tampering, Wormhole, etc. In this paper, we have provided an analysis of the layered IoT architecture. A detailed study of different types of Jamming attacks, in a wireless sensor network, is presented. The packet loss rate, energy consumption, etc. are calculated, and the performance analysis of the WSN system is achieved. The protocol chosen to evaluate the performance of the WSN is the S-MAC protocol. Different simulations are realized to evaluate the performance of a network attacked by the different types of Jamming attacks.
Hardware implementation and performance evaluation of microcontroller-based 7-level inverter using POD-SPWM technique Hajar Chadli; Sara Chadli; Mohamed Boutouba; Mohammed Saber; Abdelwahed Tahani
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 1: July 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i1.pp120-131

Abstract

Renewable energy sources are considered as inexhaustible sources for the very long-term, as they come from natural processes that are constantly replenished. However, there are a number of challenges facing renewable energy technology adoption, like the grid connecting problems. One of the main challenges relates to the grid connecting problem is the power quality issues for power converter, such as harmonics, voltage stability, and frequency fluctuation. Hence, the inverter remains the first element to be built because of its undeniable advantages in alternative continuous conversion. However, it has some disadvantages such as high component count and complex control method. This paper presents the design and implementation of a new 7-level inverter architecture with only six switches. This architecture requires fewer components compared to other 7-level inverter topologies therefore, the overall cost, control technique complexity, and conduction losses are highly reduced. A digital phase opposition disposition sinusoidal pulse width modulation (POD-SPWM) strategy using the Arduino is adopted to improve the performance of the proposed multilevel inverter (MLI) which leads to further reduction in total harmonic sistortion (THD). In this paper, the proposed inverter is tested using Proteus software and Matlab Simulink. Finally, a laboratory setup of the proposed inverter was built to validate its workability by the experimental results.
Selection of efficient machine learning algorithm on Bot-IoT dataset for intrusion detection in internet of things networks Imane Kerrakchou; Adil Abou El Hassan; Sara Chadli; Mohamed Emharraf; Mohammed Saber
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i3.pp1784-1793

Abstract

With the growth of internet of things (IoT) systems, they have become the target of malicious third parties. In order to counter this issue, realistic investigation and protection countermeasures must be evolved. These countermeasures comprise network forensics and network intrusion detection systems. To this end, a well-organized and representative data set is a crucial element in training and validating the system's credibility. In spite of the existence of multiple networks, there is usually little information provided about the botnet scenarios used. This article provides the Bot-IoT dataset that embeds traces of both legitimate and simulated IoT networks as well as several types of the attacks. It provides also a realistic test environment to address the drawbacks of existing datasets, namely capturing complete network information, precise labeling, and a variety of recent and complex attacks. Finally, this work evaluates the confidence of the Bot-IoT dataset by utilizing a variety of machine learning and statistical methods. This work will provide a foundation to enable botnet identification on IoT-specific networks.
Co-Authors Abdelwahed Tahani Adil Abou El Hassan Hajar Chadli Imane Kerrakchou Mohamed Boutouba Mohamed Emharraf Mohammed Saber Yassine Ayachi