
Future Data and Security Engineering
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
This book constitutes the refereed proceedings of the 12th International Conference on Future Data and Security Engineering, FDSE 2025, held in Ho Chi Minh City, Vietnam, during November 27-29, 2025.
The 56 full papers and 10 short papers presented in these two volumes were carefully reviewed and selected from 215 submissions.
The papers are organized in the following topical sections:
Part I: Invited Keynote; Advances in Machine Learning for Big Data Analytics; Security and Privacy Engineering; Query Processing and Optimization; Data Analytics and Healthcare Systems; Smart City and Industry 4.0 Applications.
Part II: Invited Keynote; Advances in Machine Learning for Big Data Analytics; Security and Privacy Engineering; Query Processing and Optimization; Data Analytics and Healthcare Systems; Smart City and Industry 4.0 Applications; Short Papers: Security and Data Engineering.
More details
Other editions
Additional editions

Content
.- Invited Keynote .
.- Integrating Information Systems Engineering and Life Science to Decipher the
Language of Life.
.- Advances in Machine Learning for Big Data Analytics.
.- LLM-Based Evaluation for Dynamic Routing Among Large Language Models.
.- Explainable AI for Lung Disease Classification: Looking Inside the Black Box.
.- Evaluating the SISA Framework for Efficient Machine Unlearning in Face
Recognition Models.
.- Efficient Deep Feature Embedding and Hybrid Cnn-Lstm Models for Wearable Ppg
Biometric Recognition.
.- A Dynamic Integrated Framework for Highly Accurate Real-Time Customer
Classification.
.- Security and Privacy Engineering.
.- Typical Algebraic Signature Schemes With Two Hidden Groups.
.- SCANS: A Tool for Security Vulnerability Detection in Smart Contracts.
.- Evaluation of Synthetic Data Generation for Time Series: Privacy, Security, and
Applications in Finance.
.- HeteroMalGAT: A Heterogeneous Graph Attention Network Framework for
Android Malware Detection via Knowledge Graph Representations.
.- Post-Quantum Secure Decentralized Random Number Generation Protocol with
Two Rounds of Communication in the Standard Model.
.- Query Processing and Optimization.
.- AutokRF: Efficient and Scalable Local Ensemble Learning with Automated Hyper
parameter Tuning for Large-Scale Classification.
.- HDEM: A Hierarchical Dynamic Ensemble Model for Accurate Runtime Prediction
on High Performance Computing Systems.
.- Resource-Constrained Optimization of E-Commerce Recommendation Systems.
.- Automated UML Generation: A Framework for Class Diagram Synthesis and
Multimodal Validation.
.- Data Analytics and Healthcare Systems.
.- FallTrack-Net: Real-Time Detection, Emergency Evaluation, and Mobility History
Logging in a Smartphone-Based Safety System.
.- Deep Learning Model and Fuzzy C-Means for Cardiac Disease Detection on
Electrocardiogram Signal.
.- Segmentation of Prostate Tumors Via U-Net Architecture with Convolutional
Neural Network Backbone.
.- Robust ResNet-based Models for Skin Lesion Detection.
.- Smart City and Industry 4.0 Applications.
.- UMIRA: A Unified Memory-Enhanced Retrieval and Task Allocation Framework
for Elderly Care in Smart Home Environments.
.- Evaluating YOLOv11 for Traffic Object Detection under Adverse Weather
Conditions.
.- VIESpam: A Hybrid BiLSTM Approach for Spam Classification in English and
Vietnamese SMS.
.- Predicting the stock price using Bayesian graph neural networks-based
architecture.
.- LeqLiv-25: A Ready-to-Use Malware/Benign Dataset for Training Supervised
Machine Learning Models.
.- Towards Reliable Early Fire and Smoke Detection Using Optimized YOLOv11.
.- A Multi-Agent System for Automating SDLC Documentation in IoT Environments.
.- Using a Large Language Model to Build a Vietnamese Natural Language Inference
Dataset.
.- Short Papers: Security and Data Engineering.
.- A fusion of Graph Neural Networks and Attention Mechanism for Image-Based
Recommendation Systems.
.- An efficient model for fracture detection in wrist trauma images.
.- Hybrid Deep Learning-Data Augmentation Approach for Sound Classification.
.- Improving the Louvain algorithm in community detection.
.- Lightweight ViT-Based Image Retrieval System with Qdrant for Efficient Similarity
Search.
.- Swin-FABNET: A Fuzzy Deep Learning Model For Cardiac MRI Segmentation.
.- VCaiLuong: Virtual Museum for the Preservation of Cai Luong's Artistic Heritage
and the Enhancement of Cultural Tourism Experiences.
.- Vision-based Large Language Models for Vietnamese Handwriting Recognition.
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.