Wyniki wyszukiwania - BazTech

Ograniczanie wyników

2 TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2 2025

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: Vessel Management Systems

Sortuj według:

Ogranicz wyniki do:

Genetic Algorithm for Ship Robbery Emergency Reporting System

Chang Tsai Hsin, Kao Sheng Long, Chou Chien-Chang, Chang Hsiao

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2025

Vol. 19 No. 2

609--615

In contemporary maritime navigation, ships in distress primarily rely on satellite systems in conjunction with radio systems within the framework of the Global Maritime Distress and Safety System (GMDSS) to transmit distress signals. However, the insufficient confidentiality of satellite data enables pirates engaged in ship hijacking to intercept these signals, potentially endangering the safety of hostages on board. Additionally, the high communication costs associated with satellite information transmission often discourage fishing ships from incurring these expenses. Given these cost constraints, this study seeks to develop an intelligent emergency distress notification method integrated with the Automatic Identification System (AIS). Specifically, this study introduces an innovative intelligent radio emergency notification system by incorporating the concept of radio relay stations. The proposed system integrates the Genetic Algorithm (GA) with the Maritime Geographic Information System (MGIS) as an alternative rescue method for ships in distress. The system collects all relevant information from the distressed ship through shore stations, enabling it to respond to the ship and verify the receipt of distress messages transmitted via AIS. The proposed method functions as an intermediary for distress signal transmission and confirmation. By gathering ship positions, it establishes a mobile network for message dissemination, thereby enhancing the reliability and efficiency of emergency distress communications at sea.

Artificial Intelligence in Maritime Cybersecurity: Dual-Use Applications for Defense and Offense in the Age of Digital Seas

Cichocki Rafał

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2025

Vol. 19 No. 2

617--623

The maritime sector’s rapid digital transformation – including the integration of IT and operational technology (OT) systems and the rise of autonomous vessels – has significantly expanded the cyberattack surface[1] . Artificial Intelligence (AI) now plays a dual role in this landscape, acting as both a powerful enabler of cyberattacks and a critical tool for cybersecurity defense [2] . This paper explores current and emerging uses of AI in offensive and defensive cyber operations targeting maritime systems and infrastructure. On the offensive side, threat actors are leveraging AI for sophisticated attacks such as AI-generated spear phishing, polymorphic malware generation, GPS spoofing, and manipulation of industrial control systems (ICS)[3], [4]. On the defensive side, AI is employed in anomaly detection, predictive analytics, autonomous vessel and port monitoring, and other security applications[5]. The paper also examines vulnerabilities of AI itself – including adversarial attacks, data poisoning, and model manipulation – and discusses strategies to enhance maritime cyber resilience. Key strategies include the use of digital twin simulations, AI-driven deception (honeypots), adversarial training, explainable AI, and international cooperation for information sharing. By analyzing both offensive and defensive developments, this study provides a comprehensive perspective on the dual-use nature of AI in shaping the future of maritime cybersecurity.