Processing Big Data in Motion: Core Components and System Architectures with Applications to the Maritime Domain

Abstract

Rapidly extracting business value out of Big Data that stream in corporate data centres requires continuous analysis of massive, high-speed data while they are still in motion. So challenging a goal entails that analytics should be performed in memory with a single pass over these data. In this chapter, we outline the challenges of Big streaming Data analysis for deriving real-time, online answers to application inquiries. We review approaches, architectures and systems designed to address these challenges and report on our own progress within the scope of the EU H2020 project INFORE. We showcase INFORE into a real-world use case from the maritime domain and further discuss future research and development directions.

Enhancing Maritime Cybersecurity through Operational Technology Sensor Data Fusion: A Comprehensive Survey and Analysis

“…An approach presented in ref. [ 54 ] demonstrates how an implementation using the ELK stack (Elasticsearch, Logstash, Kibana) can be used for detecting maritime anomalies. The strange/suspicious kinematic behavior of a ship, the dangerous maneuvers, malfunctions of industrial (including marine engines) or electronic equipment, and security incidents are typical anomalies.…”