Visible to the public Biblio

Filters: Author is Djemaiel, Yacine  [Clear All Filters]
2020-08-17
Djemaiel, Yacine, Fessi, Boutheina A., Boudriga, Noureddine.  2019.  Using Temporal Conceptual Graphs and Neural Networks for Big Data-Based Attack Scenarios Reconstruction. 2019 IEEE Intl Conf on Parallel Distributed Processing with Applications, Big Data Cloud Computing, Sustainable Computing Communications, Social Computing Networking (ISPA/BDCloud/SocialCom/SustainCom). :991–998.
The emergence of novel technologies and high speed networks has enabled a continually generation of huge volumes of data that should be stored and processed. These big data have allowed the emergence of new forms of complex attacks whose resolution represents a big challenge. Different methods and tools are developed to deal with this issue but definite detection is still needed since various features are not considered and tracing back an attack remains a timely activity. In this context, we propose an investigation framework that allows the reconstruction of complex attack scenarios based on huge volume of data. This framework used a temporal conceptual graph to represent the big data and the dependency between them in addition to the tracing back of the whole attack scenario. The selection of the most probable attack scenario is assisted by a developed decision model based on hybrid neural network that enables the real time classification of the possible attack scenarios using RBF networks and the convergence to the most potential attack scenario within the support of an Elman network. The efficiency of the proposed framework has been illustrated for the global attack reconstruction process targeting a smart city where a set of available services are involved.
2017-09-05
Ben Dhief, Yosra, Djemaiel, Yacine, Rekhis, Slim, Boudriga, Noureddine.  2016.  A Novel Sensor Cloud Based SCADA Infrastructure for Monitoring and Attack Prevention. Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media. :45–49.

The infrastructures of Supervisory Control and Data Acquisition (SCADA) systems have evolved through time in order to provide more efficient supervision services. Despite the changes made on SCADA architectures, several enhancements are still required to address the need for: a) large scale supervision using a high number of sensors, b) reduction of the reaction time when a malicious activity is detected; and c) the assurance of a high interoperability between SCADA systems in order to prevent the propagation of incidents. In this context, we propose a novel sensor cloud based SCADA infrastructure to monitor large scale and inter-dependant critical infrastructures, making an effective use of sensor clouds to increase the supervision coverage and the processing time. It ensures also the interoperability between interdependent SCADAs by offering a set of services to SCADA, which are created through the use of templates and are associated to set of virtual sensors. A simulation is conducted to demonstrate the effectiveness of the proposed architecture.