Alireza Dehlaghi Ghadim, Industrial Doctoral Student


Alireza Dehlaghi Ghadim is a researcher on cybersecurity of Industrial Control Systems (ICSs) focusing on using AI & ML for Intrusion detection systems (IDSs). After receiving his MSc degree in software engineering from the Sharif University of Technology (SUT), he worked as a software designer and developer in the control automation industry. This experience spiked his interest in the security of Industrial Control Systems (ICSs) and Industrial IoT solutions. Currently, he is following his research interests as a Ph.D. candidate in Mälardalens University (MDH) and as a researcher in the Research Institute of Sweden (RISE).

His research interests are Cybersecurity, Industrial Control Systems (ICS), Intrusion detection systems (IDS) and AI&ML.

[Show all publications]

Latest publications:

Enhancing Cybersecurity through Comprehensive Investigation of Data Flow-Based Attack Scenarios (Oct 2024)
Sara Abbaspour, Shamoona Imtiaz, Alireza Dehlaghi Ghadim, Mikael Sjödin, Marjan Sirjani
Journal of Cybersecurity and Privacy (JCP)

Using Decision Support to Fortify Industrial Control System against Cyberattacks (Sep 2024)
Alireza Dehlaghi Ghadim, Lars-Göran Magnusson , Niclas Ericsson, Mats Eriksson , Mahshid Helali Moghadam, Ali Balador, Hans Hansson
IEEE International Conference on Emerging Technologies and Factory Automation 2024 (ETFA 2024)

InSecTT Technologies for the Enhancement of Industrial Security and Safety (Jun 2024)
Sasikumar Punnekkat, Tijana Markovic, Miguel Leon Ortiz, Björn Leander, Alireza Dehlaghi Ghadim, Per Erik Strandberg
Intelligent Secure Trustable Things, Studies in Computational Intelligence (SCI), Springer (SCI-INSECTT)

Federated Learning for Network Anomaly Detection in a Distributed Industrial Environment (Dec 2023)
Alireza Dehlaghi Ghadim, Tijana Markovic, Miguel Leon Ortiz, David Söderman , Per Erik Strandberg
International Conference on Machine Learning and Applications 23 (ICMLA'23)

The Westermo network traffic data set (Oct 2023)
Per Erik Strandberg, David Söderman , Alireza Dehlaghi Ghadim, Miquel A. Ribot , Tijana Markovic, Sasikumar Punnekkat, David Buffoni
Data In Brief 23 (DIB 23)

Federated Learning for Network Anomaly Detection in a Distributed Industrial Environment (Aug 2023)
Alireza Dehlaghi Ghadim, Tijana Markovic, Per Erik Strandberg, David Söderman , Miguel Leon Ortiz
International Conference on Machine Learning and Applications 23 (ICMLA'23)