KPOZE Satou Aurélie Myriam

Affiliate project: CyberScada

Affiliated CEAs: University of Abomey Calavi, ACE SMIA Benin

Obafemi Awolowo University / ACE OAK-PARK

Thesis supervisor: Jules DEGILA, ACE SMIA
jules.degila@imsp-uac.org

Thesisco-supervisor: Aderounmu Ganiyu Adesola, ACE OAK-PARK
gaderoun@yahoo.com

Other contributors to thesis supervision: Abdelkader Lahmadi, INRIA
abdelkader.lahmadi@loria.fr

 

December 10th, 2021: Award Ceremony for the DSTN Hackathon, concluding the DSTN Symposium, Saint Louis, Senegal.

Start date: 01/08/21
Anticipated date of thesis defense: December 2024
ORCID profile: 0000-0002-0280-2563

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Project title: Design and optimization of smart grid SCADA architecture based on network telemetry.

Summary of scientific project: 

Industrial control systems (ICS), such as SCADA systems, are widely used in industry to automate and regulate processes. These systems rely on human-machine interfaces (HMIs) to
monitor operations, collect sensor data and control processes in sectors such as oil, gas and power. However, ICS are increasingly vulnerable to attack in today's interconnected world, not least because of connections to unsecured networks and the use of unsecured information systems and IP protocols. Traditional industrial systems, designed with minimal security in closed environments, are now exposed to the vulnerabilities of the IT world due to interconnectivity. With the rise of smart grids, which are highly digitized systems, even small flaws in SCADA systems can lead to deliberate attacks, risking system failures, material loss and personal safety. Our research aims to propose a secure SCADA architecture for Smart Grids, addressing these challenges to ensure the resilience of critical industrial processes.

Summary of results:

Following an extensive literature review including quantitative and qualitative studies [1], we carried out a risk assessment of a typical SCADA architecture in the smart grid to identify the main risks, attacks and attack vectors [2]. We then refined our contribution by proposing a new architecture based on the Software-Defined Network (SDN) paradigm. SDN is a concept in which the data plane and the control plane are decoupled, offering significant flexibility and programmability in network management and operation. We have carried out a comprehensive review of the various SDN techniques used to respond effectively to cyber attacks and guarantee the uninterrupted operation of industrial processes [3]. Our analysis covered a wide range of SDN-based security mechanisms, including intrusion detection and prevention systems, access control policies, flow-based monitoring and dynamic network reconfiguration techniques. We have developed a reconfiguration technique to mitigate Man-in-the-Middle attacks targeting a control system and affecting the synchronization of smart grids [4]. We aim to improve this algorithm by integrating Moving Target Defense (MTD) with machine learning in the SCADA architecture. MTD dynamically adjusts system configurations and network attributes in real time to increase complexity and uncertainty for potential attackers. Machine learning will refine the temporal variability of MTD.