Abstract Title

AIS Prediction to Increase Message Authenticity and Reduce Spoofing

Author Information

Jeffrey W. Icker, StudentFollow

Is this project an undergraduate, graduate, or faculty project?

Undergraduate

group

Poster Session; 10-minute Oral Presentation

Authors' Class Standing

Jeff Icker, Senior

Lead Presenter's Name

Jeff Icker

Faculty Mentor Name

Gary Kessler

Abstract

As reliance on technology continues to grow, shipborne operations have become increasingly dependent on Automatic Identification Systems (AIS) data for collision avoidance, situational awareness at sea, and navigation. The AIS protocol lacks a method to verify sender authenticity, which makes them susceptible to attacks such as message spoofing. Spoofing attacks occur when a device sends a message pretending to be another device with the intent to present misleading information, such as ship location. This report examines currently proposed methods of AIS location prediction and investigates an alternative method to achieve similar results over a shorter observation period with the intent to increase position integrity. The area of interest for this report is restricted to larger vessels which broadcast Class A messages, as they provide the most complete position snapshot and maintain the highest frequency of reports. The intended purpose of this paper is to provide a formula for single position prediction of future vessel location. A new system such as this would provide vessels a location integrity check and increase their security against spoofing attacks.

Keywords: AIS, AIS Prediction, Automatic Identification System, Single Point, Spoofing

Did this research project receive funding support (Spark or Ignite Grants) from the Office of Undergraduate Research?

Yes, Spark Grant

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AIS Prediction to Increase Message Authenticity and Reduce Spoofing

As reliance on technology continues to grow, shipborne operations have become increasingly dependent on Automatic Identification Systems (AIS) data for collision avoidance, situational awareness at sea, and navigation. The AIS protocol lacks a method to verify sender authenticity, which makes them susceptible to attacks such as message spoofing. Spoofing attacks occur when a device sends a message pretending to be another device with the intent to present misleading information, such as ship location. This report examines currently proposed methods of AIS location prediction and investigates an alternative method to achieve similar results over a shorter observation period with the intent to increase position integrity. The area of interest for this report is restricted to larger vessels which broadcast Class A messages, as they provide the most complete position snapshot and maintain the highest frequency of reports. The intended purpose of this paper is to provide a formula for single position prediction of future vessel location. A new system such as this would provide vessels a location integrity check and increase their security against spoofing attacks.

Keywords: AIS, AIS Prediction, Automatic Identification System, Single Point, Spoofing