37 citations · 73 across the 19 of their papers we have counts for
19 papers
Enhancing Web Application Firewalls with Machine Learning for SQL Injection Detection
Lilliane Linnet Musoke, Atta Badii, Ahmed Ashlam
Detecting SQL Injection (SQLi) attacks ranks among the most critical challenges in web application security. This research conducted a systematic literature review to identify the…
Enhancing Web Application Firewalls with BERT-GNN for SQL Injection Detection
Lilliane Linnet Musoke, Atta Badii, Ahmed Ashlam
Detecting sophisticated SQL Injection (SQLi) attacks remains among the most critical challenges in web applications security. This research study has resulted in an optimised hybri…
TT-DAC-PS: Twin-Target Deterministic Actor-Critic with Policy Smoothing for Optimal Trade Execution
Ilia Zaznov, Atta Badii, Julian Kunkel +1
This study addresses the optimal execution of large stock sell programs by introducing TT-DAC-PS (Twin-Target Deterministic Actor-Critic with Policy Smoothing), a deterministic act…
Fully Decentralised Consensus for Extreme-scale Blockchain
Siamak Abdi, Giuseppe Di Fatta, Atta Badii +1
Blockchain is a decentralised, immutable ledger technology that has been widely adopted in many sectors for various applications such as cryptocurrencies, smart contracts and suppl…
Blockchain Epidemic Consensus for Large-Scale Networks
Siamak Abdi, Giuseppe Di Fatta, Atta Badii +1
Blockchain is a distributed ledger technology that has applications in many domains such as cryptocurrency, smart contracts, supply chain management, and many others. Distributed c…
Stock Price Prediction Using a Hybrid LSTM-GNN Model: Integrating Time-Series and Graph-Based Analysis
Meet Satishbhai Sonani, Atta Badii, Armin Moin
This paper presents a novel hybrid model that integrates long-short-term memory (LSTM) networks and Graph Neural Networks (GNNs) to significantly enhance the accuracy of stock mark…
Enhancing SQL Injection Detection and Prevention Using Generative Models
Naga Sai Dasari, Atta Badii, Armin Moin +1
SQL Injection (SQLi) continues to pose a significant threat to the security of web applications, enabling attackers to manipulate databases and access sensitive information without…
Using Generative Models to Produce Realistic Populations of UK Windstorms
Yee Chun Tsoi, Kieran M. R. Hunt, Len Shaffrey +3
This study evaluates the potential of generative models, trained on historical ERA5 reanalysis data, for simulating windstorms over the UK. Four generative models, including a stan…
AdamZ: An Enhanced Optimisation Method for Neural Network Training
Ilia Zaznov, Atta Badii, Alfonso Dufour +1
AdamZ is an advanced variant of the Adam optimiser, developed to enhance convergence efficiency in neural network training. This optimiser dynamically adjusts the learning rate by…
Enhancing Architecture Frameworks by Including Modern Stakeholders and their Views/Viewpoints
Armin Moin, Atta Badii, Stephan Günnemann +1
Various architecture frameworks for software, systems, and enterprises have been proposed in the literature. They identified several stakeholders and defined modeling perspectives,…
Model-Driven Quantum Federated Learning (QFL)
Armin Moin, Atta Badii, Moharram Challenger
Recently, several studies have proposed frameworks for Quantum Federated Learning (QFL). For instance, the Google TensorFlow Quantum (TFQ) and TensorFlow Federated (TFF) libraries…
MDE for Machine Learning-Enabled Software Systems: A Case Study and Comparison of MontiAnna & ML-Quadrat
Jörg Christian Kirchhof, Evgeny Kusmenko, Jonas Ritz +5
In this paper, we propose to adopt the MDE paradigm for the development of Machine Learning (ML)-enabled software systems with a focus on the Internet of Things (IoT) domain. We il…
Automated Machine Learning: A Case Study on Non-Intrusive Appliance Load Monitoring
Armin Moin, Ukrit Wattanavaekin, Alexandra Lungu +2
We propose a novel approach to enable Automated Machine Learning (AutoML) for Non-Intrusive Appliance Load Monitoring (NIALM), also known as Energy Disaggregation, through Bayesian…
MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence
Armin Moin, Moharram Challenger, Atta Badii +1
Over the past decade, Artificial Intelligence (AI) has provided enormous new possibilities and opportunities, but also new demands and requirements for software systems. In particu…
ML-Quadrat & DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services
Armin Moin, Andrei Mituca, Moharram Challenger +2
In this paper, we present ML-Quadrat, an open-source research prototype that is based on the Eclipse Modeling Framework (EMF) and the state of the art in the literature of Model-Dr…
Supporting AI Engineering on the IoT Edge through Model-Driven TinyML
Armin Moin, Moharram Challenger, Atta Badii +1
Software engineering of network-centric Artificial Intelligence (AI) and Internet of Things (IoT) enabled Cyber-Physical Systems (CPS) and services, involves complex design and val…
A Model-Driven Approach to Machine Learning and Software Modeling for the IoT
Armin Moin, Moharram Challenger, Atta Badii +1
Models are used in both Software Engineering (SE) and Artificial Intelligence (AI). SE models may specify the architecture at different levels of abstraction and for addressing dif…
Collective Awareness Platforms and Digital Social Innovation Mediating Consensus Seeking in Problem Situations
Atta Badii, Franco Bagnoli, Balint Balazs +7
In this paper we show the results of our studies carried out in the framework of the European Project SciCafe2.0 in the area of Participatory Engagement models. We present a method…
Review of monitoring tools for e-learning platforms
Ali Alowayr, Atta Badii
The advancement of e-learning technologies has made it viable for developments in education and technology to be combined in order to fulfil educational needs worldwide. E-learning…