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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Habiba Chaoui
Ibn Tofail University
Computer Science & IT Electrical & Electronics Engineering

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LSTM deep learning method for network intrusion detection system Alaeddine Boukhalfa; Abderrahim Abdellaoui; Nabil Hmina; Habiba Chaoui
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (822.858 KB) | DOI: 10.11591/ijece.v10i3.pp3315-3322

Abstract

The security of the network has become a primary concern for organizations. Attackers use different means to disrupt services or steal information, these various attacks push to think of a new way to block them all in one manner. In addition, these intrusions can change and penetrate the devices of security. To solve these issues, we suggest, in this paper, a new idea for Network Intrusion Detection System (NIDS) based on Long Short-TermMemory (LSTM) to recognize menaces and to obtain a long-term memory on them, inorder to stop the new attacks that are like the existing ones, and at the sametime, to have a single mean to block intrusions. According to the results of the experiments of detections that we have carried out, the Accuracy reaches upto 99.98 % and 99.93 % for respectively the classification of two classes and several classes, Also the False Positive Rate (FPR) reaches up to only 0,068 % and 0,023 % for respectively the classification of two classes and several classes, which proves that the proposed model is very effective, it has a great ability to memorize and differentiate between normal traffic and attack traffic and its identification is more accurate than other Machine Learning classifiers.
Engaging students to fill surveys using chatbots: University case study Nadir Belhaj; Abdemounaime Hamdane; Nour El Houda Chaoui; Habiba Chaoui; Moulhime El Bekkali
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.pp473-483

Abstract

The use of chatbot or conversational agents is becoming common these days by the companies in many fields to make smart conversations with users. Backed by artificial intelligence and natural language processing they provide a strong platform to engage users. These positive aspects of chatbots can be beneficial in the educational sector, especially in conducting online survey. This study aims to explore the feasibility of a new chatbot approach survey as a new survey method in Moroccan university to overcome the web survey’s common response quality problems. Indeed, having student feedback before and after graduation is essential for university assessment. This new approach keeps students engaged, supportive, and even excited to offer feedback without getting bored and dropping the conversation, especially in Moroccan universities known by an overcrowding of students where it is difficult to get their feedback. This feedback feeds into our university' databases for further reporting and decision making to improve the quality of educational content and student-oriented services. Finally, we have shown the effectiveness of our approach by a comparative data study between the traditional online survey and the use of this chatbot.
Co-Authors Abdemounaime Hamdane Abderrahim Abdellaoui Alaeddine Boukhalfa Moulhime El Bekkali Nabil Hmina Nadir Belhaj Nour El Houda Chaoui