Using Cryptography Techniques as a Safety Mechanism Applied to Components in Autonomous Driving

  • Antonino MondelloEmail author
  • Alberto TroiaEmail author
Part of the AIRO Springer Series book series (AIROSS, volume 1)


Many applications are being developed that adopt a new emerging technology inspired by biological structures in nature to solve real-life problems; this approach involves implementations based on artificial neural networks (ANNs), deep learning, and other forms of artificial intelligence (AI). Autonomous driving is one area where these AI implementations can be applied; however, with it brings several uncertainties, including the safety and security of the implementation. The intent of this paper is to provide a new perspective in using cryptography as a methodology to implement safety in the hardware that incorporates AI technology in automotive while addressing at the same time classical problems due to physical and software failures.


Artificial intelligence Machine learning Deep learning Neural network Genetic algorithm Neuron Gene HASH HMAC SHA256 Digest Weight matrix Secure storage Memory Automotive Autonomous driving 


  1. 1.
    Yaschenko, V.V.: Cryptography: An Introduction. AMS (2002)Google Scholar
  2. 2.
    Ferguson, N. et al.: Cryptography Engineering. Wiley (2010)Google Scholar
  3. 3.
  4. 4.
    Fips-198-1. HMAC-SHA-256: Hash Based Message Authentication Code [PDF].
  5. 5.
    Hagan, M.T. et al.: Neural Network Design, 2nd ed. ISBN 978-0971732117Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Micron Technology Inc.CataniaItaly
  2. 2.Micron Technology Inc.MunichGermany

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