Risk Analysis of Pirate Attacks on Southeast Asian Ships Based on Bayesian Networks

Abstract

As a bridge for international trade, maritime transportation security is crucial to the global economy. Southeast Asian waters have become a high-incidence area of global piracy attacks due to geographic location and complex security situations, posing a great threat to the development of the Maritime Silk Road. In this study, the factors affecting the risk of pirate attacks are analyzed in depth by using the Global Ship Piracy Attacks Report from the IMO Global Integrated Shipping Information System (GISIS) database (i.e., 2013–2022) in conjunction with a Bayesian Network (BN) model, and the Expectation Maximization algorithm is used to train the model parameters. The results show that piracy behaviors and the ship’s risk are the key factors affecting the risk of pirate attacks, and suggestions are made to reduce the risk of pirate attacks. This study develops a theoretical basis for preventing and controlling the risk of pirate attacks on ships, which helps maintain the safety of ship operations.

Keywords

• piracy behaviors
• Bayesian network
• expectation maximization algorithm
• risk analysis
• global integrated shipping information system
• ship safety