DSTN Scholars

DSTN > Scholars > John EFIONG

Affiliated project: CyberSCADA

Affiliated CEA: Obafemi Awolowo University, Ile-Ife, Nigeria(ACE OAU OAK-Park)

Supervisor: Prof. G. A. Aderounmu
Obafemi Awolowo University, Ile-Ife, Nigeria(ACE OAU OAK-Park)

Co-supervisor: Prof. E. A. Olajubu
Obafemi Awolowo University, Ile-Ife, Nigeria(ACE OAU OAK-Park)

Other contributors to thesis supervision: Prof. Jules Degila

Figure 1: Architecture of the Research Methodology

DSTN > Scholars > John EFIONG

Start date: 01/01/22
Anticipated date of thesis defense: October 2024
ORCID profile: 0000-0003-4391-2475

Project title: Development of a bio-inspired multi-layer intrusion detection model for cyber-physical systems in the Smart Grid.

Summary of scientific project: 

The fusion of IT and OT in Smart Grids, orchestrated by IoT, exposes critical infrastructures to cybersecurity risks [1]. Existing Purdue-based intrusion detection systems (IDS) lack real-time threat detection and face limitations [2], [3], [4], [5], [6]. The scarcity of suitable datasets and testbeds further complicates the problem. This study aims to develop a multi-layer intrusion detection model inspired by biological mechanisms, based on machine learning, in order to improve cybersecurity in the smart grid. The aim is to design a testbed emulating smart grid protocols (IEC61850, DNP3, ModbusTCP) and create a bio-inspired adaptive IDS capable of detecting multi-level threats to critical infrastructure.

Summary of results:

Preliminary results are published in [7], [8], [9], and [10].

Scientific publications :

[1] B. Stewart et al, "A Novel Intrusion Detection Mechanism for SCADA systems which 

Automatically Adapts to Network Topology Changes," EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, vol. 4, no. 10, p. 152155, Feb. 2017, doi: 10.4108/eai.1-2-2017.152155.

[2] M. Sazzadul Hoque, "An Implementation of Intrusion Detection System Using Genetic Algorithm," International Journal of Network Security & Its Applications, vol. 4, no. 2, pp. 109-120, Mar. 2012, doi: 10.5121/ijnsa.2012.4208.

[3] B. B. Zarpelão, R. S. Miani, C. T. Kawakani, and S. C. de Alvarenga, "A survey of intrusion detection in Internet of Things," Journal of Network and Computer Applications, vol. 84, pp. 25-37, Apr. 2017, doi: 10.1016/j.jnca.2017.02.009.

[4] R. Pinto, G. Goncalves, E. Tovar, and J. Delsing, "Attack Detection in Cyber-Physical Production Systems using the Deterministic Dendritic Cell Algorithm," in 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, Sep. 2020, pp. 1552-1559. doi: 10.1109/ETFA46521.2020.9212021.

[5] R. Pinto, G. Goncalves, E. Tovar, and J. Delsing, "Attack Detection in Cyber-Physical Production Systems using the Deterministic Dendritic Cell Algorithm," IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, vol. 2020-Septe, pp. 1552-1559, 2020, doi: 10.1109/ETFA46521.2020.9212021.

[6] C. Pinto, R. Pinto, and G. Gonçalves, "Towards bio-inspired anomaly detection using the cursory dendritic cell algorithm," Algorithms, vol. 15, no. 1, pp. 1-28, 2022, doi: 10.3390/a15010001.

[7] J. E. Efiong, B. O. Akinyemi, E. A. Olajubu, G. A. Aderounmu, and J. Degila, "CyberSCADA Network Security Analysis Model for Intrusion Detection Systems in the Smart Grid," 2023, pp. 481-499. doi: 10.1007/978-3-031-24475-9_41.

[8] J. E. Efiong, A. Akinwale, B. O. Akinyemi, E. A. Olajubu, and G. A. Aderounmu, "CyberGrid: An IEC61850 Protocol-based Substation Automation Virtual Cyber Range for Cybersecurity Research in Smart Grid," Cyber-Physical Systems, 2024.

[9] J. E. Efiong, J. E. T. Akinsola, B. O. Akinyemi, E. A. Olajubu, and G. A. Aderounmu, "A Contrived Dataset of Substation Automation for Cybersecurity Research in the Smart Grid Networks based on IEC61850," TELKOMNIKA Telecommunication, Computing, Electronics and Control, 2024.

[10] J. E. Efiong, S. A. Ayanboye, O. E. Balogun, B. O. Akinyemi, E. A. Olajubu, and G. A. Aderounmu, "A Danger Theory-inspired Intrusion Detection Model for Smart Grid Cyber-Physical Systems," IET Smart Grid., 2024.

Prospects for the end of the thesis: At the end of my thesis, I will probably have acquired a global understanding of several key areas such as:
1. Understanding the integration of IT elements and physical processes in smart grid SPCs, encompassing SCADA, HMI, and PLC, and their interaction with hardware, software, and human factors.
2. Explore various IDS methodologies, including signature-based, anomaly-based and hybrid approaches, to detect unauthorized access or malicious activity in CPS environments.
3. Investigate bio-inspired computing techniques, such as artificial immune systems inspired by white blood cells, to improve intrusion detection capabilities in CPS.
4. Analyze multi-layered defense strategies to enhance CPS security by combining detection mechanisms at different layers for robust protection against cyber threats.
5. Address smart grid security challenges, such as data integrity, confidentiality issues and the potential impact of cyber-attacks on critical infrastructures.
6. Develop a new bio-inspired multi-layer intrusion detection model suitable for smart grid CPS, encompassing design, implementation and evaluation using appropriate data sets and metrics.
7. Provide new perspectives and approaches to CPS security, particularly intrusion detection, with potential implications for further research and development, improving the resilience of smart grid infrastructures to cyber threats.

Perspective after thesis completion: After completing my thesis, I will likely have gained several valuable perspectives and insights, including:
1. Specialization in the security of cyber-physical systems, particularly in smart grid domains, with an in-depth understanding of their challenges and vulnerabilities, valuable for academia and industry.
2. Development of advanced research skills, including literature review, experimental design, data analysis and model evaluation, transferable to various research fields.
3. Explore bio-inspired computational techniques, understanding their application beyond intrusion detection in areas such as optimization and machine learning.
4. Creating a new intrusion detection model for smart grids, making a significant contribution to the fields of cybersecurity and smart grid technology, and paving the way for future research.
5. Strengthen the security and resilience of critical infrastructures such as the smart grid, by effectively identifying and mitigating cyber threats.
6. Possess expertise in CPS security and research capabilities, opening up opportunities in academia, industry, government and consulting as a cybersecurity researcher, systems analyst, security architect or academic researcher.