A New Anomaly-Based Intrusion Detection System for MIL-STD-1553

Yunus Emre Ciloglu, Serif Bahtiyar

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

1 Citation (Scopus)

Abstract

MIL-STD-1553 is a communication standard developed by the US DoD in 1975 and used in military aircraft, land, and space vehicles. It enables computers and devices to interact with each other. MIL-STD-1553 is used in safety-critical systems due to its dual redundant bus structure, high reliability, and low fault rate. While the standard was considered to be secure when it was developed, MIL-STD-1553-based systems have become vulnerable and they are an easy target for attackers. In this research, we propose a new anomaly-based intrusion detection system for MIL-STD-1553 that uses machine learning for classification purposes. We experimentally evaluated the proposed system against cyber attacks. We observed that Stochastic Gradient Descent provides adequate results for the detection of intrusions on the MIL-STD-1553 bus. Overall experimental results show that the proposed system can be used to detect intrusions on MIL-STD-1553-based communications.

Original languageEnglish
Title of host publicationProceedings of 10th International Conference on Recent Advances in Air and Space Technologies, RAST 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350323023
DOIs
Publication statusPublished - 2023
Event10th International Conference on Recent Advances in Air and Space Technologies, RAST 2023 - Istanbul, Turkey
Duration: 7 Jun 20239 Jun 2023

Publication series

NameProceedings of 10th International Conference on Recent Advances in Air and Space Technologies, RAST 2023

Conference

Conference10th International Conference on Recent Advances in Air and Space Technologies, RAST 2023
Country/TerritoryTurkey
CityIstanbul
Period7/06/239/06/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • anomaly
  • avionics
  • intrusion detection
  • machine learning
  • MIL-STD-1553

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