Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Arbiter Physically Unclonable Functions (APUFs), while being relatively lightweight, are extremely vulnerable to modeling attacks. Hence, various compositions of APUFs such as XOR APUF and Lightweight Secure PUF have been proposed to be secure alternatives. Previous research has demonstrated that PUF compositions have two major challenges to overcome: vulnerability against modeling and statistical attacks, and lack of reliability. In this paper, we introduce a multiplexer-based composition of APUFs, denoted as MPUF, to simultaneously overcome these challenges. In addition to the basic MPUF design, we propose two MPUF variants namely cMPUF and rMPUF to improve the robustness against cryptanalysis and reliability-based modeling attack, respectively. An rMPUF demonstrates enhanced robustness against the reliability-based modeling attack, while even the well-known XOR APUF, otherwise robust to machine learning based modeling attacks, has been modeled using the same technique with linear data and time complexities. The rMPUF can provide a good trade-off between security and hardware overhead while maintaining a significantly higher reliability level than any practical XOR APUF instance. Moreover, MPUF variants are the first APUF compositions, to the best of our knowledge, that can achieve Strict Avalanche Criterion without using any additional input network (or hardware) for challenge transformation. Finally, we validate our theoretical findings using Matlab-based simulations of MPUFs.