Enabling Trust in IIoT: A Physec Based Approach

Christoph Lipps; Simon Duque Antón; Hans Dieter Schotten

In: Proceedings of the 14th International Conference on Cyber Warfare and Security. International Conference on Cyber Warfare and Security (ICCWS-2019), February 28 - March 1, Stellenbosch, South Africa, ACPI, 2019.


Right now we are on the verge of the fourth industrial revolution with it fusion of technologies into so-called Cyber Physical Systems (CPS), especially in the industrial sector. Accompanied by this are the modified requirements and new application scenarios, such as Machine-to-Machine (M2M) or Machine-to-Service (M2S) communication. A major driving force in this development is the ever-increasing growth of interconnected devices towards an Industrial Internet of Things (IIoT). However, it is precisely the key enablers such as mobility or flexibility with the use of wireless communication solutions, that provides risks, attack vectors and cyber security threats. Depending on the open nature and the broadcast characteristic of this transmission type, they suffer a huge potential for miscellaneous cyberattacks. That is exactly why there is a great demand for the design of new communication systems for industrial applications which includes secure communication with doubtlessly authenticated entities. All the other security services such as confidentiality, integrity or reliability are based on forgery-proof identification of these participating entities. Since conventional cryptography often comes along with a lot of overhead in form of complex computations as well as overhead in communication, both of which is not always suitable for small embedded devices and CPS applications, more lightweight security measures need to be introduced. Within this work we want to propose an approach based on the combination of different Physical Layer Security (PhySec) methods. These comprises a series of technical procedures in which the generation of cryptographic credentials is based on different physical properties. We use the conditions and characteristics of the wireless channel to apply Secret Key Generation (SKG) methods. Furthermore, we utilize slightest deviations in the manufacturing process of semiconductors such as impurities during the doping or different oxide layer thicknesses to gain a chip individual fingerprint of SRAM-cells, so-called Physically Unclonable Functions (PUFs). Our approach is a low cost, resource-saving and efficient alternative to conventional used methods.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence