Full Description
This book includes the scientific outcome of the 17th Annual International Symposium on Intelligent Distributed Systems (IDC2024) which was hosted by the University of Brighton, United Kingdom, 18-19 September 2024.
This book includes all sixteen full papers that were accepted for presentation after a rigorous peer review process by experts in their respective fields. The papers are presented here grouped in five areas of focus, namely distributed systems, cyber security, predictive modelling, blockchain applications, and large language models. They provide a wide range of areas of application that demonstrate the dynamics and constantly evolving nature of distributed systems research.
The authors work in two continents, six countries, and a total of fourteen different institutions and organizations.
The book spans different levels of progress of research, completed projects at institutional level, outcomes of PhD student work, and results that relate to large transnational projects funded by the European Union and other national and international funders.
The authors hope that the readers of this book of proceedings will find the contents informative and an opportunity to engage with new outcomes of innovative research.
The editors are:
Nikolaos Polatidis, Elias Pimenidis, Marcelo Trovati, Mehmet Aydin.
Contents
NeuroEvolution algorithms applied in the designing process of biohybrid actuators.- The Holocron: Leveraging a Dynamic 3D Matrix for Efficient Data Storage and Retrieval in Strategic Management.- Workloads Scheduling in Scientific Workflow-as-a-Service Cloud Architectures.- Hybrid Approach Using LSTM and Gradient Boosting for Accurate and Robust Store Sales Forecasting.- Enhancing IoT Security with Ensemble Deep Learning: A Lightweight, Robust Approach to Intrusion Detection.- Clustering-based Identification of Representative Security Events for Anomaly Detection in Multivariate Sensor Data.- Securing End-to-End Encrypted File Sharing Services with the Messaging Layer Security Protocol.- Anomalous Client Detection in Federated Learning.- Traditional and Bio-inspired Feature Selection for Accurate Fraud Detection.- Leveraging Deep Learning for Enhanced Software Fault Prediction Using Error-type Metrics.- A Step Towards Efficient Reduction of Ethereum's Turing-completeness.- Visualizing Bitcoin's Evolution: Dimensionality Reduction and Stylized Facts Techniques.- Trends in Intelligent Blockchain: Insights from Research Papers.- Comparative Study on Automatic Extraction of Genealogical Data from Ancient Text by Using Large Language Models and Open AI.- Planless Agents: BDI Plan Generation using LLMs.- Leveraging LLMs for Smart Cities Qualitative Data Analysis.
