Kohei Arai & Supriya Kapoor 
Advances in Information and Communication Networks [PDF ebook] 
Proceedings of the 2018 Future of Information and Communication Conference (FICC), Vol. 2

The book, gathering the proceedings of the Future of Information and Communication Conference (FICC) 2018, is a remarkable collection of chapters covering a wide range of topics in areas of information and communication technologies and their applications to the real world. It includes 104 papers and posters by pioneering academic researchers, scientists, industrial engineers, and students from all around the world, which contribute to our understanding of relevant trends of current research on communication, data science, ambient intelligence, networking, computing, security and Internet of Things. 

This book collects state of the art chapters on all aspects of information science and communication technologies, from classical to intelligent, and covers both theory and applications of the latest technologies and methodologies. 

Presenting state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research, this book is an interesting and useful resource.

The chapter “Emergency Departments” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Table des matières

Hybrid Data Mining to Reduce False Positive and False Negative Prediction in Intrusion Detection System.- Adblock Usage in Web Advertisement in Poland.- Open Algorithms for Identity Federation.- A Hybrid Anomaly Detection System for Electronic Control Units Featuring Replicator Neural Networks.- Optimizing Noise Level for Perturbing Geo-location Data.- Qualitative Analysis for Platform Independent Forensics Process Model (PIFPM) for Smartphones.- Privacy Preserving Computation in Home Loans using the FRESCO Framework.- Practically Realisable Anonymisation of Bitcoin Transactions with Improved Efficiency of the Zerocoin Protocol.- Walsh Sampling with Incomplete Noisy Signals.- Investigating the Effective use of Machine Learning Algorithms in Network Intruder Detection System