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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI)
Nawal Sael
University Hassan II of Casablanca
Computer Science & IT Electrical & Electronics Engineering Engineering

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Fake accounts detection system based on bidirectional gated recurrent unit neural network Faouzia Benabbou; Hanane Boukhouima; Nawal Sael
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp3129-3137

Abstract

Online social networks have become the most widely used medium to interact with friends and family, share news and important events or publish daily activities. However, this growing popularity has made social networks a target for suspicious exploitation such as the spreading of misleading or malicious information, making them less reliable and less trustworthy. In this paper, a fake account detection system based on the bidirectional gated recurrent unit (BiGRU) model is proposed. The focus has been on the content of users’ tweets to classify twitter user profile as legitimate or fake. Tweets are gathered in a single file and are transformed into a vector space using the GloVe word embedding technique in order to preserve the semantic and syntax context. Compared with the baseline models such as long short-term memory (LSTM) and convolutional neural networks (CNN), the results are promising and confirm that using GloVe with BiGRU classifier outperforms with 99.44% for accuracy and 99.25% for precision. To prove the efficiency of our approach the results obtained with GloVe were compared to Word2vec under the same conditions. Results confirm that GloVe with BiGRU classifier performs the best results for detection of fake Twitter accounts using only tweets content feature.
Distributed parking management architecture based on multi-agent systems Nihal El Khalidi; Faouzia Benabbou; Nawal Sael
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i4.pp801-809

Abstract

With the increase of the number of vehicles on the road, several traffic congestion problems arise in the big city, and this has a negative impact on the economy, environment and citizens. The time spent looking for a parking space and the traffic generated contributes to mobility and traffic management problems. Hence the need for smart parking management to help drivers to find vacant spaces in a car park in a shorter time. Today, researchers are considering scenarios in which a large amount of services can be offered and used by drivers and authorities to improve the management of the city's car parks and standards of quality of life. Based on literature on smart parking management system (SPMS), we have established the most important services needed such as reservation, orientation, synchronization, and security. The dynamic distributed and open aspect of the problem led us to adopt a multi-agent modeling to ensure continuous evolution and flexibility of the management system. In this conceptual paper, we propose to structure those services on a multi-agent system (MAS) that covers the whole functions of a distributed SPMS. Each service is provided as an autonomous agent, able to communicate and collaborate with the others to propose optimized parking space to customers.
Co-Authors Faouzia Benabbou Hanane Boukhouima Nihal El Khalidi