@article {Sebbar2022251,
	title = {BDA-enabler Architecture Based on Cloud Manufacturing: the Case of Chemical Industry},
	journal = {International Journal of Supply and Operations Management},
	volume = {9},
	number = {3},
	year = {2022},
	note = {cited By 0},
	pages = {251-263},
	abstract = {With the advent of cloud manufacturing (CM), alongside the maturity of specific development approaches and systems in the manufacturing industry, has led to the integration of these initiatives into Industry 4.0 to achieve higher performance. In fact, the implementation of Industry 4.0 is a real opportunity for the process industry around the world which is only at the very beginning of its deployment. However, the integration of cloud manufacturing requires the fully digitalization of industrial systems and the implementation of big data management process. Indeed, the lack of resources to handle the huge flows of data in transit and the lack of standards and interoperability is the biggest challenge to the large-scale adoption of smart manufacturing. To get around this problem, it is necessary to put in place management and analysis solutions for big data to facilitate data acquisition, process monitoring, anomaly detection and predictive and proactive maintenance. In addition, the implementation of a smart manufacturing architecture based on big data analytics (BDA) requires a lot of resources in terms of storage and computing power, which is not always available in an industrial context. Thus, it has become essential to offer suitable manufacturing models for the implementation of big data analysis services that meet the new requirements of the manufacturing sector. In this paper, a case study in one of the main African Phosphates Company will be presented. Thus, we will propose a BDA-enabler architecture based on Cloud manufacturing to identified digital opportunities and key benefits regarding performance management, production control and maintenance. The findings will help manufacturer to understand cloud manufacturing and big data analytics capabilities and take advantages from their potential and their digital opportunities to assess manufacturing process. {\textcopyright} 2022 Kharazmi University. All rights reserved.},
	doi = {10.22034/ijsom.2021.109150.2208},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140920905\&doi=10.22034\%2fijsom.2021.109150.2208\&partnerID=40\&md5=22cf4ece941e282c346700fda9fe056e},
	author = {Sebbar, A. and Zkik, K. and Belhadi, A. and Benghalia, A. and Boulmalf, M. and Ech-Cherif El Kettani, M.D.}
}
@article {Mabrouk2021,
	title = {A cooperative game based mechanism for autonomous organization and ubiquitous connectivity in VANETs},
	journal = {Simulation Modelling Practice and Theory},
	volume = {107},
	year = {2021},
	note = {cited By 7},
	abstract = {Vehicular communications in Vehicular Ad-hoc NETworks (VANETs) play an interesting role in improving traffic flow on the roads. In such wireless networks, the vehicles cooperate with each other or with the roadside infrastructure to disseminate the data. In this paper, we introduce a mechanism based on coalitional game theory to study the cooperative transmission in VANETs. Each vehicle tries to access the Internet via gateways that can be either fixed or mobile. However, these gateways help the vehicles to access the Internet by cooperatively relaying the vehicles{\textquoteright} messages. Thus, two notions to indicate the availability of transmission between vehicles and gateways are introduced. These notions are chosen to deal with the highly dynamic topology in VANETs, namely the notion of an encounter and the notion of a link{\textquoteright}s predicted lifetime. The problem is modelled as a non-transferable utility game. Then, an algorithm is proposed to dynamically form coalitions among the vehicles. Moreover, a probability of being active is set in terms of speed of the received vehicle. To evaluate the proposed solution, two scenarios are used: fixed gateways scenario and mobile gateways scenario. The numerical results show that the scenario of mobile gateways is more effective in terms of stimulating vehicles to regroup into coalitions. Hence, this helps the vehicles to access the Internet. {\textcopyright} 2020},
	keywords = {Coalitional game theory, Cooperative game, Cooperative transmission, Dynamic topologies, Game theory, Gateways (Computer networks), Non-transferable utilities, Numerical results, Probability, Vehicle transmissions, Vehicular ad hoc networks, Vehicular Adhoc Networks (VANETs), Vehicular communications},
	doi = {10.1016/j.simpat.2020.102213},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093923113\&doi=10.1016\%2fj.simpat.2020.102213\&partnerID=40\&md5=3ede889d7bb9d063f8c8265857ff2ede},
	author = {Mabrouk, A. and Naja, A. and Oualhaj, O.A. and Kobbane, A. and Boulmalf, M.}
}
@article {Sebbar2021355,
	title = {Secure Data Sharing Framework Based on Supervised Machine Learning Detection System for Future SDN-Based Networks},
	journal = {Studies in Computational Intelligence},
	volume = {919},
	year = {2021},
	note = {cited By 2},
	pages = {355-371},
	abstract = {Securing Data-sharing mechanism between Software Defined Networks (SDN) nodes represent one of the biggest challenges in SDN context. In fact, attackers may steal or perturb flows in SDN by performing several types of attacks such as address resolution protocol poisoning, main in the middle and rogue nodes attacks. These attacks are very harm full to SDN networks as they can be performed easily and passively at all SDN layers. Furthermore, data-sharing permit to an attacker to gather all sensitive flows and data from SDN architecture. In this chapter, we will propose a framework for secure data sharing that detect and stop intrusions in SDN context while ensuring authentication and privacy. To do so, we propose a defense mechanism that detect and reduce the risk of attacks based on advanced machine learning techniques. The learning and data pre-processing steps was performed by using a constructed data set dedicated to SDN context. The simulation results show that our framework can effectively and efficiently address sniffing attacks that can be detected and stopped quickly. Finally, we observe high accuracy with a low false-positive for attack detection. {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.},
	doi = {10.1007/978-3-030-57024-8_16},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097909334\&doi=10.1007\%2f978-3-030-57024-8_16\&partnerID=40\&md5=0d3b5f0a3c85d400bc35313dfe6f3009},
	author = {Sebbar, A. and Zkik, K. and Baddi, Y. and Boulmalf, M. and Ech-Cherif El Kettani, M.D.}
}
@conference {Naja2020,
	title = {Alert Message Dissemination using Graph-based Markov Decision Process Model in VANETs},
	booktitle = {IEEE International Conference on Communications},
	volume = {2020-June},
	year = {2020},
	note = {cited By 0},
	abstract = {Vehicular Ad-hoc Networks (VANETs) have many promising applications such as improving vehicle driver{\textquoteright}s safety, and so, decreasing car deaths. In VANETs, the main communication way is broadcast. Such Broadcast needs to be done efficiently especially in congested areas to avoid the broadcast storm problem. A crashed vehicle disseminates a message about its incident to all nodes in the network. The vehicle nodes of the network have to disseminate in their turn the alert message carefully to maximize both reachability and saved rebroadcast (by reducing congestion) while minimizing the delay. This concern is demonstrated and modeled by decision hypothesis. In this paper, at first, we are keen on the Markov decision process (MDP), which is utilized to model and tackle such successive decision issues. We aim to optimize a utility for each vehicle relying upon an irregular domain and choices made by it. As the MDP formalism achieves its cutoff points when it is important to consider the cooperation between the several vehicles. We will begin utilizing the Graph-based MDP where the state and activity spaces are factorizable by factors. We then demonstrate that the transition functions and rewards are deteriorated into nearby functions, and the reliance relations between the vehicles are spoken to by a graph. To Figure the optimal strategy, we use Mean Field Approximation (MFA) for tackling GMDP issue. {\textcopyright} 2020 IEEE.},
	keywords = {Accidents, Broadcast storm problem, Graphic methods, Markov decision process models, Markov Decision Processes, Markov processes, Mean field approximation, Message dissemination, Mobile telecommunication systems, Optimal strategies, Traffic congestion, Transition functions, Vehicles, Vehicular ad hoc networks, Vehicular Adhoc Networks (VANETs)},
	doi = {10.1109/ICC40277.2020.9148997},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089436123\&doi=10.1109\%2fICC40277.2020.9148997\&partnerID=40\&md5=12d16adc7ab7a4b60d7ff52c15709c2c},
	author = {Naja, A. and Oualhaj, O.A. and Boulmalf, M. and Essaaidi, M. and Kobbane, A.}
}
@article {Sebbar20205875,
	title = {MitM detection and defense mechanism CBNA-RF based on machine learning for large-scale SDN context},
	journal = {Journal of Ambient Intelligence and Humanized Computing},
	volume = {11},
	number = {12},
	year = {2020},
	note = {cited By 15},
	pages = {5875-5894},
	abstract = {Software defined network (SDN) is a promising new network abstraction that aims to improve and facilitate network management. Due to its centralized architecture and the lack of intelligence on the data plane, SDN suffers from many security issues that slows down its deployment. Man in the Middle (MitM) attack is considered as one of the most devastating attacks in an SDN context. In fact, MitM attack allows the attackers to capture, duplicate and spoof flows by targeting southbound interfaces and SDN nodes. Furthermore, it{\textquoteright}s very difficult to detect MitM attacks since it is performed passively at the SDN level. To reduce the impact of this attack, we generally set up security policies and authentication mechanisms. However, these techniques are not applicable for a large scale SDN architecture as they require complexes and static configurations and as they negatively influence on network performance. In this paper, we propose an intrusion detection and prevention framework by using machine learning techniques to detect and stop MitM attempts. To do so, we build a context-based node acceptance based on the random forest model (CBNA-RF), which helps to setting-up appropriate security policies and to automating defense operations on a large-scale SDN context. This mechanism can realize a quick and early detection of MitM attacks by automatically detecting malicious nodes without affecting performances. The evaluation of the proposed framework demonstrates that our model can correctly classify and detect malicious connections and nodes while keeping high accuracy and precision scores. {\textcopyright} 2020, Springer-Verlag GmbH Germany, part of Springer Nature.},
	keywords = {Authentication mechanisms, Centralized architecture, Decision trees, Defense operations, Intrusion detection, Intrusion detection and prevention, Machine learning, Machine learning techniques, Man-In-The-Middle (MITM) Attack, Network abstractions, Network architecture, Network security, Random forest modeling, Security systems},
	doi = {10.1007/s12652-020-02099-4},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085987877\&doi=10.1007\%2fs12652-020-02099-4\&partnerID=40\&md5=cf120767ba875958e97b87ce22203057},
	author = {Sebbar, A. and Zkik, K. and Baddi, Y. and Boulmalf, M. and Kettani, M.D.E.-C.E.}
}
@article {Baddi2020245,
	title = {Msnd: Multicast software defined network based solution to multicast tree construction},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {12293},
	year = {2020},
	note = {cited By 0},
	pages = {245-256},
	abstract = {Internet services provider propose increasingly numerous applications depend on multicast communication patterns, such as database synchronization, newsletter updates, video, and audio group streaming. In spite of, IP multicast is frequently suffered from scaling and instability, which causes internet provider administrators to avoid its utilization. While different multicast protocols in all layers, such as routing and switching, have been created by researchers and providers, through several years, to focus on security, congestion control, and scalability, our work aims to scale multicast regarding the number of supported multicast groups and sources in networks and multicast session. In this paper, we propose an SDN-based IP multicast tree construction module to support and deploy multicast communication-based services. To do so, we take advantage to compute multicast tree, in the centralized way, to achieve a dynamic tree construction algorithm that helps SDN controller to dynamically construct and adjust an optimal multicast tree in all multicast session. The experiments studies on the prototype and simulation system exhibit that our solution gives better performance contrasted with the traditional multicast tree construction algorithms, better also to SDN-based solution proposed in the literature, regarding multicast tree cost, delay, delay variation, and multicast tree construction delay. {\textcopyright} Springer Nature Switzerland AG 2020.},
	keywords = {Database synchronization, Forestry, Internet protocols, Internet services providers, Multicast communication, Multicast protocol, Multicast sessions, Multicast software, Multicast tree construction, Multicasting, Network security, Overlay networks, Simulation systems, Software defined networking, Trees (mathematics), Ubiquitous computing},
	doi = {10.1007/978-3-030-58008-7_20},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096412695\&doi=10.1007\%2f978-3-030-58008-7_20\&partnerID=40\&md5=f5004a1fb0f79381fe80ca313ad89b13},
	author = {Baddi, Y. and Sebbar, A. and Zkik, K. and Boulmalf, M. and El Kettani, M.D.E.-C.}
}
@conference {Bekkali2019,
	title = {Securing the Internet of Things (IoT)},
	booktitle = {Proceedings - 2018 International Conference on Wireless Networks and Mobile Communications, WINCOM 2018},
	year = {2019},
	note = {cited By 0},
	doi = {10.1109/WINCOM.2018.8629652},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062838771\&doi=10.1109\%2fWINCOM.2018.8629652\&partnerID=40\&md5=384b7ebf423613c054b0ec7d89c21c6a},
	author = {Bekkali, A.E. and Boulmalf, M. and Essaaidi, M. and Mezzour, G.}
}
@conference {Sebbar2018583,
	title = {Detection MITM Attack in Multi-SDN Controller},
	booktitle = {Colloquium in Information Science and Technology, CIST},
	volume = {2018-October},
	year = {2018},
	pages = {583-587},
	doi = {10.1109/CIST.2018.8596479},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061446244\&doi=10.1109\%2fCIST.2018.8596479\&partnerID=40\&md5=04ea13257b17af4ec26de2fe0c9aeba7},
	author = {Sebbar, A. and Boulmalf, M. and Dafir Ech-Cherif El Kettani, M. and Badd, Y.}
}
@conference {ElKhaddar2012440,
	title = {Emerging wireless technologies in e-health: Trends, challenges, and framework design issues},
	booktitle = {Proceedings of 2012 International Conference on Multimedia Computing and Systems, ICMCS 2012},
	year = {2012},
	note = {cited By 20},
	pages = {440-445},
	doi = {10.1109/ICMCS.2012.6320276},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869803375\&doi=10.1109\%2fICMCS.2012.6320276\&partnerID=40\&md5=3f8a7111cfa37918453a942aa23762f3},
	author = {El Khaddar, M.A. and Harroud, H. and Boulmalf, M. and Elkoutbi, M. and Habbani, A.}
}
@article {Ajana201119,
	title = {FlexRFID middleware in the supply chain: Strategic values and challenges},
	journal = {International Journal of Mobile Computing and Multimedia Communications},
	volume = {3},
	number = {2},
	year = {2011},
	note = {cited By 0},
	pages = {19-32},
	doi = {10.4018/jmcmc.2011040102},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052879454\&doi=10.4018\%2fjmcmc.2011040102\&partnerID=40\&md5=3256e261ddc2de34d29749a6b36fe5bf},
	author = {Ajana, M.E. and Harroud, H. and Boulmalf, M. and Elkoutbi, M.}
}
