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Naval Cybersecurity in the Age of AI: deceptive ISAR Images Generation with GANs
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  • Giulio Meucci ,
  • Bertan Karahoda ,
  • Amir Hossein Oveis ,
  • Francesco Mancuso ,
  • Edmond Jajaga ,
  • Alessandro Cantelli-Forti
Giulio Meucci
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Bertan Karahoda
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Amir Hossein Oveis
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Francesco Mancuso
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Edmond Jajaga
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Alessandro Cantelli-Forti

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Navigational systems, the heart of maritime oper- ations, face escalating cybersecurity risks due to their system of systems nature and reliance on diverse suppliers. Amid concerns about supply chain attacks and insider threats, the potential for malicious radar image injections, including Inverse Synthetic Aperture Radar (ISAR) images, is emerging. Such manipulations can critically undermine navigational integrity through the generation of decoy targets, the strategic relocation of existing ones, and the effective concealment of additional targets. We have identified where an Advanced Persistent Threat (APT) could be concealed within the processing chain of a modern radar system. This study demonstrates the potential of APTs to exploit Generative Adversarial Networks (GANs) for the creation of deceptive ISAR images, thereby spotlighting this previously unexplored threat vector. Our findings offer novel insights into bolstering maritime cybersecurity in an increasingly AI-dominated landscape.