Alireza Dehlaghi Ghadim

Alireza Dehlaghi Ghadim

Educational background

Sharif University of Technology, Tehran, Iran

M.Sc., Software Engineering, Jan 2012

Thesis Topic: A Performance Evaluation of Grid Scheduling Algorithms based on Market Theory

Area of Study: Grid Computing, Economical Grid, Graph Theory, Game Theory, Algorithm Design

Iran University of Science and Technology, Tehran, Iran

B.Sc., Software Engineering, Aug 2009

Thesis Topic: Investigation of bug discovery and locating in software systems, A survey

Area of Study: Software Testing, Graph Theory

Work Experience

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).

Research Topic

Identification of Cyberattacks in Industrial Control Systems

Research Abstract

With the increased use of ICS(Industrial control systems )cybersecurity has become a major concern. One of the challenges of securing ICS is that many ICS are built on legacy systems. These old systems were not designed with cybersecurity in mind, making them vulnerable to modern cyber threats. One way to protect ICSs against cyberattacks is by using advanced intrusion detection techniques that rely on machine learning algorithms. In this research, we explore how well different types of machine learning algorithms can be used to create effective intrusion detection systems. Additionally, we investigate to what extent the algorithms can distinguish different attack types.

His research domain is Cybersecurity of Industrial Control Systems (ICSs) and designing Intrusion detection systems (IDSs) using AI&ML. Cyber attacks take the system from its normal function and leave traces on the system state variable or network data. Therefore, advanced AI algorithms such as convolutional neural networks and time series AI could help IDS find cyber attacks using remained data traces from attacks.  


InSecTT Project

InSecTT – Intelligent Secure Trustable Things, a pan-European effort with 52 key partners from 12 countries (EU and Turkey), will provide intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together. InSecTT aims at creating trust in AI-based intelligent systems and solutions as a major part of the AIoT. 

Role: Researcher on cybersecurity of Industrial Control Systems (ICSs) focusing on Intrusion detection systems (IDSs) using AI & ML approaches. 

IndTech Industrial Technology Graduate School

The deployment of such transformative industrial digital technologies in manufacturing and process industries is the core focus of the INDTECH industrial graduate school.

Role: Industrial PhD student.

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