Following Moore's law, the density of integrated circuits is increasing in all dimensions, for instance, in 3D stacked chip networks. Amongst other electro-optic solutions, multimode optical interconnects on a silicon interposer promise to enable high throughput for modern hardware platforms in a restricted space. Such integrated architectures require confidential communication between multiple chips as a key factor for high-performance infrastructures in the 5G era and beyond. Physical layer security is an approach providing information theoretic security among network participants, exploiting the uniqueness of the data channel. We experimentally project orthogonal and non-orthogonal symbols through 380 μm long multimode on-chip interconnects by wavefront shaping. These interconnects are investigated for their uniqueness by repeating these experiments across multiple channels and samples. We show that the detected speckle patterns resulting from modal crosstalk can be recognized by training a deep neural network, which is used to transform these patterns into a corresponding readable output. The results showcase the feasibility of applying physical layer security to multimode interconnects on silicon interposers for confidential optical 3D chip networks.
Keywords: deep neural network; multimode optical interconnect; physical layer security; silicon interposer; through-silicon via; wavefront shaping.