Artificial Intelligence-Enabled Exploratory Cyber-Physical Safety Analyzer Framework for Civilian Urban Air Mobility

Md Shirajum Munir, Sumit Howlader Dipro, Kamrul Hasan, Tariqul Islam, Sachin Shetty

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Urban air mobility (UAM) has become a potential candidate for civilization for serving smart citizens, such as through delivery, surveillance, and air taxis. However, safety concerns have grown since commercial UAM uses a publicly available communication infrastructure that enhances the risk of jamming and spoofing attacks to steal or crash crafts in UAM. To protect commercial UAM from cyberattacks and theft, this work proposes an artificial intelligence (AI)-enabled exploratory cyber-physical safety analyzer framework. The proposed framework devises supervised learning-based AI schemes such as decision tree, random forests, logistic regression, K-nearest neighbors (KNN), and long short-term memory (LSTM) for predicting and detecting cyber jamming and spoofing attacks. Then, the developed framework analyzes the conditional dependencies based on the Pearson’s correlation coefficient among the control messages for finding the cause of potential attacks based on the outcome of the AI algorithm. This work considers the UAM attitude control scenario for determining jam and spoofing attacks as a use case to validate the proposed framework with a state-of-the-art UAV attack dataset. The experiment results show the efficacy of the proposed framework in terms of around (Formula presented.) accuracy for jamming and spoofing detection with a decision tree, random forests, and KNN while efficiently finding the root cause of the attack.

Original languageEnglish (US)
Article number755
JournalApplied Sciences (Switzerland)
Issue number2
StatePublished - Jan 2023


  • artificial intelligence
  • attitude control
  • exploratory cyber-physical safety analyzer
  • jamming
  • spoofing
  • urban air mobility (UAM)

ASJC Scopus subject areas

  • General Materials Science
  • Instrumentation
  • General Engineering
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes


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