Institute of Informatics
Topic
Artificial Intelligence Methods in Cyber Security
PhD. program
Informatics / Applied Informatics
Name of the supervisor
doc. Ing. Ladislav Hluchý, CSc.
Contact:
Receiving school
Faculty of Mathematics, Physics and Informatics, Comenius Uni in Bratislava
Annotation
Receiving schools (another possibilities):
- Faculty of Electrical Engineering and Informatics, Technical Uni of Košice (FEI TUKE, program: Informatics)
- Faculty of Informatics and Information Technologies of STU in Bratislava (program: Applied Informatics)
Most current approaches to computer security focus on specific aspects of information and communication technology systems such as access control, cryptography, anonymization, virus protection, antivirus detection, intrusion detection, and anomaly detection. However, they lack an overall view of many aspects of cyber threats and do not pay due attention to one of the most important elements of cyber security: the human aspect. In addition, they often fail to address the dynamic nature of cyber attacks that are rapidly evolving and become more sophisticated by using new vulnerabilities and combining various attack channels (network, physical, human, etc.). To address these constraints and to increase our detection and response capabilities, we need a systematic and holistic approach to cyber security that takes into account technological and human factors. The dissertation project will focus on the design of methodology and methods for the analysis of anomalies and abnormalities using techniques of data acquisition and machine learning (data mining and processes mining) with the possibility of detection of hitherto unknown threats and vulnerabilities.
more info
year 2022/2023
- Faculty of Electrical Engineering and Informatics, Technical Uni of Košice (FEI TUKE, program: Informatics)
- Faculty of Informatics and Information Technologies of STU in Bratislava (program: Applied Informatics)
Most current approaches to computer security focus on specific aspects of information and communication technology systems such as access control, cryptography, anonymization, virus protection, antivirus detection, intrusion detection, and anomaly detection. However, they lack an overall view of many aspects of cyber threats and do not pay due attention to one of the most important elements of cyber security: the human aspect. In addition, they often fail to address the dynamic nature of cyber attacks that are rapidly evolving and become more sophisticated by using new vulnerabilities and combining various attack channels (network, physical, human, etc.). To address these constraints and to increase our detection and response capabilities, we need a systematic and holistic approach to cyber security that takes into account technological and human factors. The dissertation project will focus on the design of methodology and methods for the analysis of anomalies and abnormalities using techniques of data acquisition and machine learning (data mining and processes mining) with the possibility of detection of hitherto unknown threats and vulnerabilities.
more info
year 2022/2023