@conference {Bouijij2022, title = {Phishing URL classification using Extra-Tree and DNN}, booktitle = {10th International Symposium on Digital Forensics and Security, ISDFS 2022}, year = {2022}, note = {cited By 0}, abstract = {Machine Learning (ML) and Deep Learning (DL) methods have become indispensable in cybersecurity. Recently, they are often used to detect and classify phishing websites. Phishing websites are a major problem that has a negative impact on organization and of societies. Statistics report that the number of phishing website is continuously increasing and it is becoming more difficult to detect them. Various works have shown that ML and DL can be efficient to solve this problem. In this work, we adopted lexical analysis and Tiny URL approaches for URL features extraction. The accuracy metric obtained surpasses 98\% for Extra Tree algorithm and can achieve 99\% for Deep Neural Network model. {\textcopyright} 2022 IEEE.}, keywords = {Computer crime, Cyber security, Cybercriminals, Cybersecurity, Deep learning, Deep neural networks, Evaluation metrics, Extra-trees, Forestry, Learning systems, Lexical analysis, Machine-learning, Phishing, Tiny URL, Trees (mathematics), URL, Websites}, doi = {10.1109/ISDFS55398.2022.9800795}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134218804\&doi=10.1109\%2fISDFS55398.2022.9800795\&partnerID=40\&md5=65081aa39ffad3c05f668a253be030fb}, author = {Bouijij, H. and Berqia, A. and Saliah-Hassan, H.} } @article {Bennouri20225746, title = {U-NewReno transmission control protocol to improve TCP performance in Underwater Wireless Sensors Networks}, journal = {Journal of King Saud University - Computer and Information Sciences}, volume = {34}, number = {8}, year = {2022}, note = {cited By 0}, pages = {5746-5758}, abstract = {Advances in the different fields of application on Underwater Wireless Sensor Networks (UWSNs) makes this environment more attractive for researchers and industry. Communication in this environment faces exceptional challenges, since its data transmission is experiencing a limitation in the use of bandwidth, the presence of surrounding noise and also the long delays of acoustic propagation. It is of great benefit to design an adaptive transmission control protocol (TCP) for the underwater environment. In this work, we propose U-New Reno a transmission control protocol suitable for the marine environment wherein we consider both the adaptation of the maximum size of the congestion window and the expiry of the round-trip time (RTT). U-New Reno can achieve a very significant improvement concerning the retransmission rate of the packets and the evolution of the number of packets delivered. The performances of both metrics are closely observed during the comparison of simulation results between the standard New Reno and our proposed U-New Reno. {\textcopyright} 2021 King Saud University}, doi = {10.1016/j.jksuci.2021.08.006}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114818664\&doi=10.1016\%2fj.jksuci.2021.08.006\&partnerID=40\&md5=3a92e142cf64f316d890032a44316881}, author = {Bennouri, H. and Berqia, A. and Patrick, N.K.} } @conference {Bouijij2021, title = {Machine Learning Algorithms Evaluation for Phishing URLs Classification}, booktitle = {2021 4th International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2021}, year = {2021}, note = {cited By 2}, abstract = {Phishing URL is a type of cyberattack, based on falsified URLs. The number of phishing URL attacks continues to increase despite cybersecurity efforts. According to the Anti-Phishing Working Group (APWG), the number of phishing websites observed in 2020 is 1 520 832, doubling over the course of a year. Various algorithms, techniques and methods can be used to build models for phishing URL detection and classification. From our reading, we observed that Machine Learning (ML) is one of the recent approaches used to detect and classify phishing URL in an efficient and proactive way. In this paper, we evaluate eleven of the most adopted ML algorithms such as Decision Tree (DT), Nearest Neighbours (KNN), Gradient Boosting (GB), Logistic Regression (LR), Na{\"\i}ve Bayes (NB), Random Forest (RF), Support Vector Machines (SVM), Neural Network (NN), Ex-tra_Tree (ET), Ada_Boost (AB) and Bagging (B). To do that, we compute detection accuracy metric for each algorithm and we use lexical analysis to extract the URL features. {\textcopyright} 2021 IEEE.}, keywords = {Accuracy metric, Adaptive boosting, Algorithm evaluation, Computational linguistics, Computer crime, Cyber security, Cyber-attacks, Cybersecurity, Decision trees, Feature, Lexical analysis, Logistic regression, Machine learning algorithms, Phishing, Phishing-URL, Random forests, Support vector machines}, doi = {10.1109/ISAECT53699.2021.9668489}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124953329\&doi=10.1109\%2fISAECT53699.2021.9668489\&partnerID=40\&md5=6054cb867f24686cb4af1bf450094608}, author = {Bouijij, H. and Berqia, A.} } @conference {Bennouri2019, title = {Controlling Maximum Window of TCP NewReno in Underwater Wireless Sensor Network}, booktitle = {International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2018 - Proceedings}, year = {2019}, note = {cited By 0}, doi = {10.1109/ISAECT.2018.8618752}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062465101\&doi=10.1109\%2fISAECT.2018.8618752\&partnerID=40\&md5=daaf3cb63078453cd6c0ebaf34f2b957}, author = {Bennouri, H. and Berqia, A. and Patrick, N.K.} } @conference {Bennouri2018121, title = {The Impact of TCP Packet Size and Number of TCP Connections in Underwater Wireless Sensor Networks}, booktitle = {Proceedings on 2018 International Conference on Advances in Computing and Communication Engineering, ICACCE 2018}, year = {2018}, pages = {121-126}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053482125\&partnerID=40\&md5=16e3f1a3bc79c1ec9fcfb29ec0a50988}, author = {Bennouri, H. and Berqia, A.} } @conference {Bennouri2018112, title = {A pursuit learning solution to underwater communications with limited mobility agents}, booktitle = {Proceedings of the 2018 Research in Adaptive and Convergent Systems, RACS 2018}, year = {2018}, pages = {112-117}, doi = {10.1145/3264746.3264798}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056895227\&doi=10.1145\%2f3264746.3264798\&partnerID=40\&md5=aa7cd573ad4e924d806689aceb8057a6}, author = {Bennouri, H. and Yazidi, A. and Berqia, A.} } @article {Ouhbi2017181, title = {Editorial}, journal = {Journal of Mobile Multimedia}, volume = {13}, number = {3-4}, year = {2017}, note = {cited By 0}, pages = {181-182}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040221877\&partnerID=40\&md5=0aafa6f210492195dfab7b876d509c51}, author = {Ouhbi, B. and Berqia, A.} } @article {Gourmaj2017244, title = {Teaching power electronics and digital electronics using personal learning environments. from traditional learning to remote experiential learning}, journal = {Journal of Mobile Multimedia}, volume = {13}, number = {3-4}, year = {2017}, note = {cited By 0}, pages = {244-255}, abstract = {Practical works have a fundamental role in the curriculum of any scientist, engineer, and technician. It helps learners to face the real world and put in practice what they have learned to judge their operability. Moreover, due to some limiting factors and due to the growth number of learners, universities and institutes have become inapt to give efficient learning. Distance education presents a future key to reduce these restrictions. Currently, remote experiments together with web-based courses approach significantly contribute many aspects of education for learners. In this context, the main question addressed is how we ensure that an educational system evolves to better serve the needs of learners? The present work proposes a solution based on student{\textquoteright}s Personal Learning Environments {\textquoteright}PLEs{\textquoteright}. PLEs are educational platforms that help learners take control and manage their own learning process, learning modules with remote experiments, for reaching a specific goal. In order to response these criteria we use the Learning Management System (LMS) Moodle, the e-portfolio Mahara, the Remote Laboratory Management System (RLMS) iLab Shared Architecture (ISA) with additional tools and plug-ins to implement the learning by doing environment. {\textcopyright} Rinton Press.}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040225241\&partnerID=40\&md5=bf688a5ec5060678e1ed74d6a4e98bad}, author = {Gourmaj, M. and Naddami, A. and Fahli, A. and Berqia, A.} } @article {Daoui2012137, title = {Mobility prediction and location management based on data mining}, journal = {International Conference on Next Generation Networks and Services, NGNS}, year = {2012}, note = {cited By 1}, pages = {137-140}, doi = {10.1109/NGNS.2012.6656095}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894186087\&doi=10.1109\%2fNGNS.2012.6656095\&partnerID=40\&md5=5539050c158dd348e89a347da6abd380}, author = {Daoui, M. and Belkadi, M. and Chamek, L. and Lalam, M. and Hamrioui, S. and Berqia, A.} } @conference {Angoma2011101, title = {HaVe-2W3G: A vertical handoff solution between WLAN, WiMAX and 3G networks}, booktitle = {IWCMC 2011 - 7th International Wireless Communications and Mobile Computing Conference}, year = {2011}, note = {cited By 8}, pages = {101-106}, doi = {10.1109/IWCMC.2011.5982514}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052450203\&doi=10.1109\%2fIWCMC.2011.5982514\&partnerID=40\&md5=678334f04e9317df81cc23e2cd3ea407}, author = {Angoma, B. and Erradi, M. and Benkaouz, Y. and Berqia, A. and Charaf Akalay, M.} } @conference {Blaise2009, title = {Can MAC waiting time improve TCP performance over ad-hoc networks?}, booktitle = {2009 Mediterrannean Microwave Symposium, MMS 2009}, year = {2009}, note = {cited By 0}, doi = {10.1109/MMS.2009.5409805}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950326540\&doi=10.1109\%2fMMS.2009.5409805\&partnerID=40\&md5=0a1ec2421fc7897e9d936bfb0c49fb0b}, author = {Blaise, A. and Berqia, A.} } @conference {Berqia200816, title = {Fairness and QoS in ad-hoc networks}, booktitle = {IEEE Vehicular Technology Conference}, year = {2008}, note = {cited By 2}, pages = {16-20}, doi = {10.1109/VETECS.2008.16}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-47749084749\&doi=10.1109\%2fVETECS.2008.16\&partnerID=40\&md5=4f700df4d5db788cc77adca79f873bb9}, author = {Berqia, A. and Angoma, B. and Mikou, N. and Dehbi, Y.} }