Earth Virtualization Engines -- A Technical Perspective

Participants of the Berlin Summit on Earth Virtualization Engines (EVEs) discussed ideas and concepts to improve our ability to cope with climate change. EVEs aim to provide interactive and accessible climate simulations and data for a wide range of users. They combine high-resolution physics-based models with machine learning techniques to improve the fidelity, efficiency, and interpretability of climate projections. At their core, EVEs offer a federated data layer that enables simple and fast access to exabyte-sized climate data through simple interfaces. In this article, we summarize the technical challenges and opportunities for developing EVEs, and argue that they are essential for addressing the consequences of climate change.

Hardware Obfuscation of Digital FIR Filters

A finite impulse response (FIR) filter is a ubiquitous block in digital signal processing applications. Its characteristics are determined by its coefficients, which are the intellectual property (IP) for its designer. However, in a hardware efficient realization, its coefficients become vulnerable to reverse engineering. This paper presents a filter design technique that can protect this IP, taking into account hardware complexity and ensuring that the filter behaves as specified only when a secret key is provided. To do so, coefficients are hidden among decoys, which are selected beyond possible values of coefficients using three alternative methods. As an attack scenario, an adversary at an untrusted foundry is considered. A reverse engineering technique is developed to find the chosen decoy selection method and explore the potential leakage of coefficients through decoys. An oracle-less attack is also used to find the secret key. Experimental results show that the proposed technique can lead to filter designs with competitive hardware complexity and higher resiliency to attacks with respect to previously proposed methods.