A Survey of Security Challenges in Automatic Identification System (AIS) Protocol

Silvie Levy, Ehud Gudes, Danny Hendler

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The world of maritime transport is a significant part of the global economy. Traffic control relies, among other means, on the Automatic Identification System (AIS) device, which reports dynamic and fixed data. Vessels use advanced cyber capabilities to falsify data that the AIS transmits and impersonate an innocent ship while carrying out illegal activity, especially the vessel’s location data, without control. A significant part of the work done to find false AIS reports looks for location reports. Each AIS device uses a transceiver based on SOTDMA (Self-Organized TDMA) and determines its transmission schedule (slot) based on data link traffic history and an awareness of other stations’ possible actions. The SOTDMA protocol was developed in the late 1990s and does not have built-in security features, which leaves communication networks vulnerable to cyber threats such as eavesdropping, tampering with data, unauthorized access, and cyber-attacks. This Protocol is widely used in wireless communication systems where no central authority manages the communication between nodes, dynamically adjusts to changes in network topology, and nodes can come and go at any time. This article reviews the cybersecurity challenges in the AIS protocol used in vessels. Most of those challenges imply a variety of areas using SOTDMA protocols like Wireless Sensors (WSNs), Mobile (MANETs), Military, Disaster Relief Networks, Healthcare Monitoring Systems, Industrial Automation Systems, Vehicle-to-Vehicle (V2V) Communication Networks, Wireless Metropolitan Area Networks (WMANs), Internet of Things (IoT) Networks, and Machine-to-Machine (M2M) Communication Networks.

Original languageEnglish
Title of host publicationCyber Security, Cryptology, and Machine Learning - 7th International Symposium, CSCML 2023, Proceedings
EditorsShlomi Dolev, Ehud Gudes, Pascal Paillier
PublisherSpringer Science and Business Media Deutschland GmbH
Pages411-423
Number of pages13
ISBN (Print)9783031346705
DOIs
StatePublished - 1 Jan 2023
Event7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023 - Be'er Sheva, Israel
Duration: 29 Jun 202330 Jun 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13914 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023
Country/TerritoryIsrael
CityBe'er Sheva
Period29/06/2330/06/23

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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