TY - GEN
T1 - Trustworthiness Verification and Integrity Testing for Wireless Communication Systems
AU - Boche, Holger
AU - Schaefer, Rafael F.
AU - Poor, H. Vincent
AU - Fettweis, Gerhard P.
N1 - Funding Information:
This work of H. Boche was supported in part by the German Federal Ministry of Education and Research (BMBF) within the national initiative on 6G Communication Systems through the research hub 6G-life under Grant 16KISK002, within the national initiative for Post Shannon Communication (NewCom) under Grant 16KIS1003K, and the project Hardware Platforms and Computing Models for Neuromorphic Computing (NeuroCM) under Grant 16ME0442. It has further received funding by the Bavarian Ministry of Economic Affairs, Regional Development and Energy as part of the project 6G Future Lab Bavaria as well as in part by the German Research Foundation (DFG) within Germany’s Excellence Strategy EXC-2092 – 390781972. This work of R. F. Schaefer was supported in part by the BMBF within NewCom under Grant 16KIS1004 and in part by the DFG under Grant SCHA 1944/6-1. This work of H. V. Poor was supported by the U.S. National Science Foundation under Grant CCF-1908308. This work of G. P. Fettweis was supported in part by the BMBF within 6G-Plattform under Grant 16KISK051.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Trustworthiness verification and integrity testing have been identified as key challenges for the sixth generation (6G) of mobile networks and its variety of envisioned features. In this paper, these issues are addressed from a fundamental, algorithmic point of view. For this purpose, the concept of Turing machines is used which provides the fundamental performance limits of digital computers. It is shown that, in general, trustworthiness and integrity cannot be verified by Turing machines and therewith by today's digital computers. In addition, the trustworthiness problem is further shown to be non-Banach-Mazur computable which is the weakest form of computability. Neuromorphic computing has an enormous potential to overcome the limitations of today's digital hardware and, accordingly, it is interesting to study the issues of trustworthiness verification and integrity testing also for such powerful computing models. In particular, as considerable progress in the hardware design for neuromorphic computing has been achieved.
AB - Trustworthiness verification and integrity testing have been identified as key challenges for the sixth generation (6G) of mobile networks and its variety of envisioned features. In this paper, these issues are addressed from a fundamental, algorithmic point of view. For this purpose, the concept of Turing machines is used which provides the fundamental performance limits of digital computers. It is shown that, in general, trustworthiness and integrity cannot be verified by Turing machines and therewith by today's digital computers. In addition, the trustworthiness problem is further shown to be non-Banach-Mazur computable which is the weakest form of computability. Neuromorphic computing has an enormous potential to overcome the limitations of today's digital hardware and, accordingly, it is interesting to study the issues of trustworthiness verification and integrity testing also for such powerful computing models. In particular, as considerable progress in the hardware design for neuromorphic computing has been achieved.
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U2 - 10.1109/ICC45855.2022.9838877
DO - 10.1109/ICC45855.2022.9838877
M3 - Conference contribution
AN - SCOPUS:85136282002
T3 - IEEE International Conference on Communications
SP - 4830
EP - 4835
BT - ICC 2022 - IEEE International Conference on Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Communications, ICC 2022
Y2 - 16 May 2022 through 20 May 2022
ER -