The Artificial Intelligence the Strategic Key of Cybersecurity

Cyber defense intelligence: the Strategic Key of Cybersecurity




Artificial Intelligence, Data Mining, Classification, Classifiers based on Ensemble, Machine Learning, Parallel Computing, Computer Security, Electrical Research


Despite the fact that digital transformation introduces multiple advantages, it also introduces crucial security challenges, since it combines heterogeneous communications, the integration of digital devices, legacy technologies. In the case of power grid, in addition to damage to the availability, integrity and confidentiality of information; there may be manipulation and take control of assets through the infection of operational systems. In this context, powerful cybersecurity schemes and mechanisms that guarantee the safe transmission of information and the safe operation of assets are required. The goal is develop cyber security schemes and mechanisms based on intelligent cyber defense mechanisms that provide flexibility and self-learning capacity to support humans in the analysis and generation of containment measures against cyber-attacks. This paper presents the developed and validation of an Intrusion Detection and Prediction System (IDPS) based on individual classifiers and ensemble algorithms. The IDPS has demonstrated be an efficient countermeasure against several cyberattacks. The proposed IDPS uses J48 (decision tree), CLONAL-G (artificial immune system), bayesian classifier and ensemble algorithm and was validated with the KDDCup databases. The attacks in the data set are categorized into four attack types: DoS (denial-of-service attacks), R2L (root-to-local attacks), U2R (user-to-root attack), and Probe (probing attacks). The results show that the individual classifiers perform well for particular attack, so it was necessary to build an ensemble algorithm that combine the information from each classifier for better performance. The idea is not to rely on a single classifier for the decision, but rather individual information from different classifiers is combined to make the final decision.

Author Biography

Gustavo Arroyo-Figueroa, INEEL

Gustavo Arroyo-Figueroa completed his Ph.D. in Computer Science at Monterrey Institute of Technology and his undergraduate studies at the Celaya Institute of Technology. Currently, is head and researcher in the area of Information Technologies at Instituto Nacional de Electricidad y Energías Limpias. His research includes developed of information systems and Applied Artificial Intelligence for power systems. For more than 30 years, he has worked in Artificial Intelligence applications for Electric Power Utilities for task of automation, intelligent control, Diagnosis, Prediction, Forecasting, Data Driven Smart Energy Management, Smart Grid, Intelligent Learning and Intelligent computer security. Dr. Arroyo-Figueroa has published over 100 journal and congress papers published in national and international journals and conferences. He is reviewer for several national and international journals and he has held various roles in scientific committees of congress and meetings. He is member of National Research System of Mexico and board of the Mexican Society of Artificial Intelligence and national member of SC D2 CIGRE (Information systems and Communications). Recently collaborate in the group CIGRE JWG D2/C2.41 Advanced Utility Data Management and Analytics for Improved Situational Awareness of EPU Operations (TB 732) and currently collaborate in the group CIGRE D2/2.52 Artificial Intelligent Applications and Technology in Power Industry. His subjects of interest are Machine Learning, Data Science, Big Data Analytics, Applied Artificial Intelligence, and Smart Grid.




How to Cite

Arroyo-Figueroa, G. (2023). The Artificial Intelligence the Strategic Key of Cybersecurity: Cyber defense intelligence: the Strategic Key of Cybersecurity . International Journal of Combinatorial Optimization Problems and Informatics, 14(3), 16–23.