3-hydroxyisobutyrate dehydrogenase is involved in both, valine and isoleucine degradation in arabidopsis thaliana

In plants, amino acid catabolism is especially relevant in metabolic stress situations (e.g. limited carbohydrate availability during extended darkness). Under these conditions, amino acids are used as alternative substrates for respiration. Complete oxidation of the branched-chain amino acids (BCAAs) leucine, isoleucine (Ile), and valine (Val) in the mitochondria efficiently allows the formation of ATP by oxidative phosphorylation. However, the metabolic pathways for BCAA breakdown are largely unknown so far in plants. A systematic search for Arabidopsis (Arabidopsis thaliana) genes encoding proteins resembling enzymes involved in BCAA catabolism in animals, fungi, and bacteria as well as proteomic analyses of mitochondrial fractions from Arabidopsis allowed the identification of a putative 3-hydroxyisobutyrate dehydrogenase, AtHDH1 (At4g20930), involved in Val degradation. Systematic substrate screening analyses revealed that the protein uses 3-hydroxyisobutyrate but additionally 3-hydroxypropionate as substrates. This points to a role of the enzyme not only in Val but possibly also in Ile metabolism. At4g20930 knockdown plants were characterized to test this conclusion. Root toxicity assays revealed increased root growth inhibition of the mutants if cultivated in the presence of Val or Ile but not in the presence of leucine. We conclude that AtHDH1 has a dual role in BCAA metabolism in plants

Secure Multiparty Computation from Threshold Encryption Based on Class Groups

We construct the first actively-secure threshold version of the cryptosystem based on class groups from the so-called CL~framework (Castagnos and Laguillaumie, 2015). We show how to use our threshold scheme to achieve general universally composable (UC) secure multiparty computation (MPC) with only transparent set-up, i.e., with no secret trapdoors involved. On the way to our goal, we design new zero-knowledge (ZK) protocols with constant communication complexity for proving multiplicative relations between encrypted values. This allows us to use the ZK proofs to achieve MPC with active security with only a constant factor overhead. Finally, we adapt our protocol for the so-called You-Only-Speak-Once (YOSO) setting, which is a very promising recent approach for performing MPC over a blockchain. This is possible because our key generation protocol is simpler and requires significantly less interaction compared to previous approaches: in particular, our new key generation protocol allows the adversary to bias the public key, but we show that this has no impact on the security of the resulting cryptosystem

MOTION - A Framework for Mixed-Protocol Multi-Party Computation

We present MOTION, an efficient and generic open-source framework for mixed-protocol secure multi-party computation (MPC). MOTION is built in a user-friendly, modular, and extensible way, intended to be used as tool in MPC research and to increase adoption of MPC protocols in practice. Our framework incorporates several important engineering decisions such as full communication serialization, which enables MPC over arbitrary messaging interfaces and removes the need of owning network sockets. MOTION also incorporates several novel performance optimizations that improve the communication complexity and latency, e.g., 2x better online round complexity of precomputed correlated Oblivious Transfer (OT). We instantiate our framework with protocols for N parties and security against up to N-1 passive corruptions: the MPC protocols of Goldreich-Micali-Wigderson (GMW) in its arithmetic and Boolean version and OT-based BMR (Ben-Efraim et al., CCS\u2716), as well as novel and highly efficient conversions between them, including a non-interactive conversion from BMR to arithmetic GMW. MOTION is highly efficient, which we demonstrate in our experiments. Compared to secure evaluation of AES-128 with N=3 parties in a high-latency network with OT-based BMR, we achieve a 16x better throughput of 16 AES evaluations per second using BMR. With this, we show that BMR is much more competitive than previously assumed. For N=3 parties and full-threshold protocols in a LAN, MOTION is 10x-18x faster than the previous best passively secure implementation from the MP-SPDZ framework, and 190x-586x faster than the actively secure SCALE-MAMBA framework. Finally, we show that our framework is highly efficient for privacy-preserving neural network inference

Ramen: Souper Fast Three-Party Computation for RAM Programs

Secure RAM computation allows a number of parties to evaluate a function represented as a random-access machine (RAM) program in a way that reveals nothing about the private inputs of the parties except from what is already revealed by the function output itself. In this work we present \emph{Ramen}, which is a new protocol for computing RAM programs securely among three parties, tolerating up to one passive corruption. Ramen provides reasonable asymptotic guarantees and is concretely efficient at the same time. We have implemented our protocol and provide extensive benchmarks for various settings. Asymptotically, our protocol requires a constant number of rounds and an amortized sublinear amount of communication and computation per memory access. In terms of concrete efficiency, our protocol outperforms previous solutions. For a memory of size $2^{26}$ our memory accesses are $25\times$ faster in the LAN and $8\times$ faster in the WAN setting, when compared to the previously fastest, and concurrent, solution by Vadapalli, Henry, and Goldberg (USENIX Security 2023). Due to our superior asymptotic guarantees, the efficiency gap is only widening as the memory gets larger and for this reason Ramen provides the currently most scalable concretely efficient solution for securely computing RAM programs

FUSE – Flexible File Format and Intermediate Representation for Secure Multi-Party Computation

Secure Multi-Party Computation (MPC) is continuously becoming more and more practical. Many optimizations have been introduced, making MPC protocols more suitable for solving real-world problems. However, the MPC protocols and optimizations are usually implemented as a standalone proof of concept or in an MPC framework and are tightly coupled with special-purpose circuit formats, such as Bristol Format. This makes it very hard and time-consuming to re-use algorithmic advances and implemented applications in a different context. Developing generic algorithmic optimizations is exceptionally hard because the available MPC tools and formats are not generic and do not provide the necessary infrastructure. In this paper, we present FUSE: A Framework for Unifying and Optimizing Secure Multi-Party Computation Implementations with Efficient Circuit Storage. FUSE provides a flexible intermediate representation (FUSE IR) that can be used across different platforms and in different programming languages, including C/C++, Java, Rust, and Python. We aim at making MPC tools more interoperable, removing the tight coupling between high-level compilers for MPC and specific MPC protocol engines, thus driving knowledge transfer. Our framework is inspired by the widely known LLVM compiler framework. FUSE is portable, extensible, and it provides implementation-agnostic optimizations. As frontends, we implement HyCC (CCS\u2718), the Bristol circuit format, and MOTION (TOPS\u2722), meaning that these can be automatically converted to FUSE IR. We implement several generic optimization passes, such as automatic subgraph replacement and vectorization, to showcase the utility and efficiency of our framework. Finally, we implement as backends MOTION and MP-SPDZ (CCS\u2720), so that FUSE IR can be run by these frameworks in an MPC protocol, as well as other useful backends for JSON output and the DOT language for graph visualization. With FUSE, it is possible to use any implemented frontend with any implemented backend and vice-versa. FUSE IR is not only efficient to work on and much more generic than any other format so far -- supporting, e.g., function calls, hybrid MPC protocols as well as user-defined building blocks, and annotations -- while maintaining backwards-compatibility, but also compact, with smaller storage size than even minimalistic formats such as Bristol already for a few hundred operations

Publicly Verifiable Zero-Knowledge and Post-Quantum Signatures From VOLE-in-the-Head

We present a new method for transforming zero-knowledge protocols in the designated verifier setting into public-coin protocols, which can be made non-interactive and publicly verifiable. Our transformation applies to a large class of ZK protocols based on oblivious transfer. In particular, we show that it can be applied to recent, fast protocols based on vector oblivious linear evaluation (VOLE), with a technique we call VOLE-in-the-head, upgrading these protocols to support public verifiability. Our resulting ZK protocols have linear proof size, and are simpler, smaller and faster than related approaches based on MPC-in-the-head. To build VOLE-in-the-head while supporting both binary circuits and large finite fields, we develop several new technical tools. One of these is a new proof of security for the SoftSpokenOT protocol (Crypto 2022), which generalizes it to produce certain types of VOLE correlations over large fields. Secondly, we present a new ZK protocol that is tailored to take advantage of this form of VOLE, which leads to a publicly verifiable VOLE-in-the-head protocol with only 2x more communication than the best, designated-verifier VOLE-based protocols. We analyze the soundness of our approach when made non-interactive using the Fiat-Shamir transform, using round-by-round soundness. As an application of the resulting NIZK, we present FAEST, a post-quantum signature scheme based on AES. FAEST is the first AES-based signature scheme to be smaller than SPHINCS+, with signature sizes between 5.6 and 6.6kB at the 128-bit security level. Compared with the smallest version of SPHINCS+ (7.9kB), FAEST verification is slower, but the signing times are between 8x and 40x faster

The OpenModelica integrated environment for modeling, simulation, and model-based development

OpenModelica is a unique large-scale integrated open-source Modelica- and FMI-based modeling, simulation, optimization, model-based analysis and development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; Modelica- UML integration; requirement verification; and generation of parallel code for multi-core architectures. The environment is based on the equation-based object-oriented Modelica language and currently uses the MetaModelica extended version of Modelica for its model compiler implementation. This overview paper gives an up-to-date description of the capabilities of the system, short overviews of used open source symbolic and numeric algorithms with pointers to published literature, tool integration aspects, some lessons learned, and the main vision behind its development.Fil: Fritzson, Peter. Linköping University; SueciaFil: Pop, Adrian. Linköping University; SueciaFil: Abdelhak, Karim. Fachhochschule Bielefeld; AlemaniaFil: Asghar, Adeel. Linköping University; SueciaFil: Bachmann, Bernhard. Fachhochschule Bielefeld; AlemaniaFil: Braun, Willi. Fachhochschule Bielefeld; AlemaniaFil: Bouskela, Daniel. Electricité de France; FranciaFil: Braun, Robert. Linköping University; SueciaFil: Buffoni, Lena. Linköping University; SueciaFil: Casella, Francesco. Politecnico di Milano; ItaliaFil: Castro, Rodrigo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Franke, Rüdiger. Abb Group; AlemaniaFil: Fritzson, Dag. Linköping University; SueciaFil: Gebremedhin, Mahder. Linköping University; SueciaFil: Heuermann, Andreas. Linköping University; SueciaFil: Lie, Bernt. University of South-Eastern Norway; NoruegaFil: Mengist, Alachew. Linköping University; SueciaFil: Mikelsons, Lars. Linköping University; SueciaFil: Moudgalya, Kannan. Indian Institute Of Technology Bombay; IndiaFil: Ochel, Lennart. Linköping University; SueciaFil: Palanisamy, Arunkumar. Linköping University; SueciaFil: Ruge, Vitalij. Fachhochschule Bielefeld; AlemaniaFil: Schamai, Wladimir. Danfoss Power Solutions GmbH & Co; AlemaniaFil: Sjolund, Martin. Linköping University; SueciaFil: Thiele, Bernhard. Linköping University; SueciaFil: Tinnerholm, John. Linköping University; SueciaFil: Ostlund, Per. Linköping University; Sueci