@conference {Kasmi20181,
	title = {Performance evaluation of StarPU schedulers with preconditioned conjugate gradient solver on heterogeneous (multi-CPUs/multi-GPUs) architecture},
	booktitle = {Proceedings of 2017 International Conference of Cloud Computing Technologies and Applications, CloudTech 2017},
	volume = {2018-January},
	year = {2018},
	pages = {1-6},
	doi = {10.1109/CloudTech.2017.8284742},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046664197\&doi=10.1109\%2fCloudTech.2017.8284742\&partnerID=40\&md5=15d1bacdcdc6b413b42b5bc9c3059bfb},
	author = {Kasmi, N. and Zbakh, M. and Samadi, Y. and Cherkaoui, R. and Haouari, A.}
}
@article {Cherkaoui2017206,
	title = {Performance analysis of intrusion detection systems in cloud-based systems},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {10542 LNCS},
	year = {2017},
	note = {cited By 0},
	pages = {206-213},
	abstract = {Cloud computing services are widely used nowadays and need to be more secured for an effective exploitation by the users. One of the most challenging issues in these environments is the security of the hosted data. Many cloud computing providers offer web applications for their clients, this is why the most handling attacks in cloud computing are Distributed Denial of Service (DDoS). In this paper, we provide a comparative performance analysis of intrusion detection systems (IDSs) in a real world lab. The aim is to provide an up to date study for researchers and practitioners to understand the issues related to intrusion detection and to deal with DDoS attacks. This analysis includes intrusion detection rates, time running, etc. In the experiments, we configured a cloud platform using OpenStack and an IDS monitoring the whole network traffic of the web server configured. The results show that Suricata drops fewer packets than Bro and Snort successively when a DDoS attack is happening and detect more malicious packets. {\textcopyright} Springer International Publishing AG 2017.},
	doi = {10.1007/978-3-319-68179-5_18},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034613510\&doi=10.1007\%2f978-3-319-68179-5_18\&partnerID=40\&md5=3e0ce668710d845db260ee41dabb49b5},
	author = {Cherkaoui, R. and Zbakh, M. and Braeken, A. and Touhafi, A.}
}
@conference {Harraz2017230,
	title = {Study of an adaptive approach for a Cloud system implementation},
	booktitle = {Proceedings of 2016 International Conference on Cloud Computing Technologies and Applications, CloudTech 2016},
	year = {2017},
	note = {cited By 0},
	pages = {230-236},
	abstract = {In the few recent years a new paradigm has emerged, with the onward steps that revolutionized the internet and the machines interconnected over it. This has lead the modern technological world to be considered as a virtual sphere interconnecting things using internet, being called the Cloud Computing where any object can communicate with any other object using a network such as the internet. The Cloud Computing makes it possible for end users to profit from the high speed and high performance of remote machines, and deploys a business where internet providers can implement distributed resources and services based on modern technologies to address the needs of the end users. In such paradigm, all components should work in a fashion to provide the best response time possible, one way of doing that is through load balancing algorithms. In this paper we propose a cloud load balancing algorithm that relates to the stochastic and random behavior of any networking system, we show as a result that we can achieve a game theoretic load balancing policy based on the samples of the load in time. {\textcopyright} 2016 IEEE.},
	doi = {10.1109/CloudTech.2016.7847704},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013764269\&doi=10.1109\%2fCloudTech.2016.7847704\&partnerID=40\&md5=34d05b50f0f8af7eb7ee1964533a0ebd},
	author = {Harraz, A. and Bissiriou, C. and Cherkaoui, R. and Zbakh, M.}
}
@conference {Zbakh2015,
	title = {A multi-criteria analysis of intrusion detection architectures in cloud environments},
	booktitle = {Proceedings of 2015 International Conference on Cloud Computing Technologies and Applications, CloudTech 2015},
	year = {2015},
	note = {cited By 0},
	abstract = {Cloud computing promises to increase innovation and the velocity with which applications are deployed all while helping any enterprise meet most IT service needs at a lower total cost of ownership and higher return investment. As the March of cloud continues, it brings both new opportunities and new security challenges. To take advantage of those opportunities while minimizing risks, we argue that Intrusion Detection Systems (IDS) integrated in the cloud is one of the best existing solutions nowadays in the field. The concept of intrusion detection was known since past and was first proposed in 1980s. Since that time IDSs are evolving. However, even several efforts have been made in the area of Intrusion Detection Systems for cloud computing environment, many attacks still prevail. Therefore, the work presented in this paper proposes a multi-criteria analysis and a comparative study between several IDS architectures designed to work in cloud computing environments. To achieve this objective, in the first place we will search in the state of the art for several consistent IDS architectures designed to work in a cloud environment. Whereas, in a second step we will establish the criteria that will be useful for the evaluation of architectures. Later, using the approach of multi-criteria decision analysis MacBeth (Measuring Attractiveness by a Categorical Based Evaluation Technique) we will evaluate the criteria and assign to each one the appropriate weight according to their importance in the field of IDS architectures in cloud computing. The last step is to evaluate architectures against the criteria and collecting results of the model constructed in the previous steps. {\textcopyright} 2015 IEEE.},
	doi = {10.1109/CloudTech.2015.7336967},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962845309\&doi=10.1109\%2fCloudTech.2015.7336967\&partnerID=40\&md5=1128e7690631b70d9247248b05a81a50},
	author = {Zbakh, M. and Elmahdi, K. and Cherkaoui, R. and Enniari, S.}
}
