65 citations · 70 across the 14 of their papers we have counts for
15 papers
Alleviating Attack Data Scarcity: SCANIA's Experience Towards Enhancing In-Vehicle Cyber Security Measures
Frida Sundfeldt, Bianca Widstam, Mahshid Helali Moghadam +2
The digital evolution of connected vehicles and the subsequent security risks emphasize the critical need for implementing in-vehicle cyber security measures such as intrusion dete…
LLM-based Property-based Test Generation for Guardrailing Cyber-Physical Systems
Khashayar Etemadi, Marjan Sirjani, Mahshid Helali Moghadam +2
Cyber-physical systems (CPSs) are complex systems that integrate physical, computational, and communication subsystems. The heterogeneous nature of these systems makes their safety…
A Maritime Industry Experience for Vessel Operational Anomaly Detection: Utilizing Deep Learning Augmented with Lightweight Interpretable Models
Mahshid Helali Moghadam, Mateusz Rzymowski, Lukasz Kulas
This study presents an industry experience showcasing a vessel operational anomaly detection approach that utilizes semi-supervised deep learning models augmented with lightweight…
Anomaly Detection Dataset for Industrial Control Systems
Alireza Dehlaghi-Ghadim, Mahshid Helali Moghadam, Ali Balador +1
Over the past few decades, Industrial Control Systems (ICSs) have been targeted by cyberattacks and are becoming increasingly vulnerable as more ICSs are connected to the internet.…
Making Sense of Failure Logs in an Industrial DevOps Environment
Muhammad Abbas, Ali Hamayouni, Mahshid Helali Moghadam +2
Processing and reviewing nightly test execution failure logs for large industrial systems is a tedious activity. Furthermore, multiple failures might share one root/common cause du…
ICSSIM-A Framework for Building Industrial Control Systems Security Simulation Testbeds
Alireza Dehlaghi-Ghadim, Ali Balador, Mahshid Helali Moghadam +2
With the advent of smart industry, Industrial Control Systems (ICS) are increasingly using Cloud, IoT, and other services to meet Industry 4.0 targets. The connectivity inherent in…
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System
Markus Borg, Jens Henriksson, Kasper Socha +7
Integration of Machine Learning (ML) components in critical applications introduces novel challenges for software certification and verification. New safety standards and technical…
Machine Learning Testing in an ADAS Case Study Using Simulation-Integrated Bio-Inspired Search-Based Testing
Mahshid Helali Moghadam, Markus Borg, Mehrdad Saadatmand +3
This paper presents an extended version of Deeper, a search-based simulation-integrated test solution that generates failure-revealing test scenarios for testing a deep neural netw…
HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space
Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin +3
The human mental search (HMS) algorithm is a relatively recent population-based metaheuristic algorithm, which has shown competitive performance in solving complex optimisation pro…
Efficient and Effective Generation of Test Cases for Pedestrian Detection -- Search-based Software Testing of Baidu Apollo in SVL
Hamid Ebadi, Mahshid Helali Moghadam, Markus Borg +3
With the growing capabilities of autonomous vehicles, there is a higher demand for sophisticated and pragmatic quality assurance approaches for machine learning-enabled systems in…
An LSTM-based Plagiarism Detection via Attention Mechanism and a Population-based Approach for Pre-Training Parameters with imbalanced Classes
Seyed Vahid Moravvej, Seyed Jalaleddin Mousavirad, Mahshid Helali Moghadam +1
Plagiarism is one of the leading problems in academic and industrial environments, which its goal is to find the similar items in a typical document or source code. This paper prop…
An Enhanced Differential Evolution Algorithm Using a Novel Clustering-based Mutation Operator
Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin +3
Differential evolution (DE) is an effective population-based metaheuristic algorithm for solving complex optimisation problems. However, the performance of DE is sensitive to the m…
Performance Testing Using a Smart Reinforcement Learning-Driven Test Agent
Mahshid Helali Moghadam, Golrokh Hamidi, Markus Borg +4
Performance testing with the aim of generating an efficient and effective workload to identify performance issues is challenging. Many of the automated approaches mainly rely on an…
Automated Performance Testing Based on Active Deep Learning
Ali Sedaghatbaf, Mahshid Helali Moghadam, Mehrdad Saadatmand
Generating tests that can reveal performance issues in large and complex software systems within a reasonable amount of time is a challenging task. On one hand, there are numerous…
An Autonomous Performance Testing Framework using Self-Adaptive Fuzzy Reinforcement Learning
Mahshid Helali Moghadam, Mehrdad Saadatmand, Markus Borg +2
Test automation brings the potential to reduce costs and human effort, but several aspects of software testing remain challenging to automate. One such example is automated perform…