@conference {Elhachimi2022,
	title = {Secure Internet of Thing using Blockchain Technology},
	booktitle = {2022 7th International Conference on Smart and Sustainable Technologies, SpliTech 2022},
	year = {2022},
	note = {cited By 0},
	abstract = {With their vast range of uses, Internet of things (IoT) and its applications are becoming more popular. However, the security and privacy of the IoT-based applications remains a worry. The majority of the privacy and security issues of the interconnected, diverse resource-constrained IoT devices are unable to be solved efficiently by traditional security protocols. Blockchain technology has emerged as a distributed ledger technology or data structure that can manage many intelligent IoT transactions and ensure greater security to data management. In this paper, we propose a light-weight authentication system based Blockchain approach that provides network and communication security. Due to Blockchain decentralized nature and transparency, the proposed approach ensures high-level data security, improves system operation efficiency and system performances. {\textcopyright} 2022 University of Split, FESB.},
	keywords = {Authentication systems, Block-chain, Blockchain, Data privacy, Distributed ledger, Information management, Internet of thing security, Internet of things, ITS applications, Light weight, Network security, Privacy and security, Privacy issue, Security and privacy, Security issues, Security protocols},
	doi = {10.23919/SpliTech55088.2022.9854376},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138143921\&doi=10.23919\%2fSpliTech55088.2022.9854376\&partnerID=40\&md5=166e29d5aefdeeb4fac8936bf1150d04},
	author = {Elhachimi, J. and Kobbane, A.}
}
@article {Abouaomar2022,
	title = {Service Function Chaining in MEC: A Mean-Field Game and Reinforcement Learning Approach},
	journal = {IEEE Systems Journal},
	year = {2022},
	note = {cited By 0},
	pages = {1-12},
	abstract = {Multiaccess edge computing (MEC) and network virtualization technologies are important enablers for fifth generation networks to deliver diverse services. Services are often provided as fully connected virtual network functions (VNFs), through service function chaining (SFC). However, the problem of allocating SFC resources at the edge still faces many challenges related to the way VNFs are placed, chained, and scheduled. In this article, to solve these problems, we propose a game theory-based approach with the objective to reduce service latency in the context of SFC at the edge. The problem of allocating SFC resources can be divided into two subproblems: 1) the VNF placement and routing subproblem, and 2) the VNF scheduling subproblem. For the former subproblem, we formulate it as a mean-field game in which VNFs are contending over edge resources aiming at reducing the resource consumption of MEC nodes and reducing latency for users. We also propose a reinforcement learning-based technique, where the Ishikawa{\textendash}Mann learning algorithm is used. For the later subproblem, we formulate it as a matching game between VFNs and edge resources to find the execution order of the VNFs while reducing the latency. To efficiently solve it, we propose a modified version of the many-to-one deferred acceptance algorithm (DAA), called the enhanced multistep DAA. To illustrate the performance of the proposed approaches, we perform extensive simulations. The results show that the approaches achieve up to 40\% less resource consumption, and up to 38\% less latency than the benchmarked state-of-the-art methods. IEEE},
	keywords = {Computation theory, Computer games, Edge computing, Game, Game theory, Learning algorithms, Network function virtualization, Problem solving, Processor scheduling, Reinforcement learning, Resource allocation, Resource allocation/provisioning, Resource Management, Resources allocation, Routings, Scheduling, Service function chaining, Service functions, Transfer functions, Virtual reality, Virtualizations},
	doi = {10.1109/JSYST.2022.3171232},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131721006\&doi=10.1109\%2fJSYST.2022.3171232\&partnerID=40\&md5=e7ecad4d011f9a66bf06f1e9f3f4d176},
	author = {Abouaomar, A. and Cherkaoui, S. and Mlika, Z. and Kobbane, A.}
}
@conference {Gryech2021,
	title = {On spatial prediction of urban air pollution},
	booktitle = {2021 17th International Conference on Intelligent Environments, IE 2021 - Proceedings},
	year = {2021},
	note = {cited By 0},
	abstract = {Air pollution continues to draw global attention, and still causes adverse environmental issues and health effects. Questions about how air pollution evolves spatially are also still unsolved. Many air quality monitoring stations are deployed in several countries to give insight about air quality. However, it is quite frequent for these stations to go out of order during their long life time. These incidents may lead to a significant loss of pollution data. To mitigate this issue, we propose to leverage spatial correlation between pollution monitoring stations to predict the lost data. To reduce the complexity of the prediction model, for each monitoring station, we identify the best set of other stations to use in the prediction model. Correlation-based station selection is shown to outperform distance-based station selection and provides an R2 above 0.8 when applied to the Airparif datasets. {\textcopyright} 2021 IEEE.},
	keywords = {Air quality, Air quality monitoring stations, Environmental issues, Forecasting, Intelligent agents, Monitoring stations, Pollution monitoring, Prediction model, Predictive analytics, Spatial correlations, Spatial prediction, Urban air pollution},
	doi = {10.1109/IE51775.2021.9486618},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114499832\&doi=10.1109\%2fIE51775.2021.9486618\&partnerID=40\&md5=10a04db251b0bca163abb4d34f0c721a},
	author = {Gryech, I. and Ben-Aboud, Y. and Ghogho, M. and Kobbane, A.}
}
@conference {Filali2018,
	title = {SDN Controller Assignment and Load Balancing with Minimum Quota of Processing Capacity},
	booktitle = {IEEE International Conference on Communications},
	volume = {2018-May},
	year = {2018},
	doi = {10.1109/ICC.2018.8422750},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051428081\&doi=10.1109\%2fICC.2018.8422750\&partnerID=40\&md5=950211c49ab90c21d84d57b5ecf8c58f},
	author = {Filali, A. and Kobbane, A. and Elmachkour, M. and Cherkaoui, S.}
}
@conference {Mabrouk2018495,
	title = {Signaling game-based approach to improve security in vehicular networks},
	booktitle = {VEHITS 2018 - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems},
	volume = {2018-March},
	year = {2018},
	pages = {495-500},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051947337\&partnerID=40\&md5=fd17d3ff35b56253285bf7d433abcfa8},
	author = {Mabrouk, A. and Kobbane, A. and El Koutbi, M.}
}
@conference {Aitfares2017113,
	title = {Suspicious behavior detection of people by monitoring camera},
	booktitle = {International Conference on Multimedia Computing and Systems -Proceedings},
	year = {2017},
	note = {cited By 0},
	pages = {113-117},
	abstract = {The analytic video is a very challenging area of research in computer vision. Ensure a high level of security in a public space monitored by a surveillance camera is a difficult task in recent years. Understanding people behaviors in real time allows the surveillance systems to analyze unusual events through the video frames. In this paper, we propose a new approach for detecting suspicious behavior of moving people. We are not interested in a simple motion detection of a moving object, but we analyze the trajectory of this latter; relying on the object motion vector. Once a suspicious behavior suddenly occurs in this trajectory, we segment and track this object during its motion within the camera{\textquoteright}s field of view. Experiments with real-world images validate the efficiency of the proposed approach. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/ICMCS.2016.7905601},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019074005\&doi=10.1109\%2fICMCS.2016.7905601\&partnerID=40\&md5=72fbf7b2e7ea117ae6bf2217a9fdc658},
	author = {Aitfares, W. and Kobbane, A. and Kriouile, A.}
}
