CrypTen: Secure Multi-Party Computation Meets Machine Learning

Secure multi-party computation (MPC) allows parties to perform computations on data while keeping that data private. This capability has great potential for machine-learning applications: it facilitates training of machine-learning models on private data sets owned by different parties, evaluation of one party's private model using another party's private data, etc. Although a range of studies implement machine-learning models via secure MPC, such implementations are not yet mainstream. Adoption of secure MPC is hampered by the absence of flexible software frameworks that "speak the language" of machine-learning researchers and engineers. To foster adoption of secure MPC in machine learning, we present CrypTen: a software framework that exposes popular secure MPC primitives via abstractions that are common in modern machine-learning frameworks, such as tensor computations, automatic differentiation, and modular neural networks. This paper describes the design of CrypTen and measure its performance on state-of-the-art models for text classification, speech recognition, and image classification. Our benchmarks show that CrypTen's GPU support and high-performance communication between (an arbitrary number of) parties allows it to perform efficient private evaluation of modern machine-learning models under a semi-honest threat model. For example, two parties using CrypTen can securely predict phonemes in speech recordings using Wav2Letter faster than real-time. We hope that CrypTen will spur adoption of secure MPC in the machine-learning community

CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

We introduce CryptGPU, a system for privacy-preserving machine learning that implements all operations on the GPU (graphics processing unit). Just as GPUs played a pivotal role in the success of modern deep learning, they are also essential for realizing scalable privacy-preserving deep learning. In this work, we start by introducing a new interface to losslessly embed cryptographic operations over secret-shared values (in a discrete domain) into floating-point operations that can be processed by highly-optimized CUDA kernels for linear algebra. We then identify a sequence of GPU-friendly cryptographic protocols to enable privacy-preserving evaluation of both linear and non-linear operations on the GPU. Our microbenchmarks indicate that our private GPU-based convolution protocol is over 150x faster than the analogous CPU-based protocol; for non-linear operations like the ReLU activation function, our GPU-based protocol is around 10x faster than its CPU analog. With CryptGPU, we support private inference and private training on convolutional neural networks with over 60 million parameters as well as handle large datasets like ImageNet. Compared to the previous state-of-the-art, when considering large models and datasets, our protocols achieve a 2x to 8x improvement in private inference and a 6x to 36x improvement for private training. Our work not only showcases the viability of performing secure multiparty computation (MPC) entirely on the GPU to enable fast privacy-preserving machine learning, but also highlights the importance of designing new MPC primitives that can take full advantage of the GPU\u27s computing capabilities

A comparative analysis of biogas and hydrogen, and the impact of the certificates and blockchain new paradigms

Solar and wind energy technologies, due to their nature of weather dependency, have been recognized as not the complete solution for the renewable energy transition. Creating a solution for the short fall is empirical if we are to remove the dependency on fossil fuels and reach net zero targets. The production of hydrogen, biogas and other gases can be produced sustainably, which can also allow for the utilization of waste materials or the ability to store energy and allow a greater positive impact on our environment. However, production of these gases is not always as transparent or environmentally friendly as perceived, so with the aid of certification and blockchain, we can create a system that can guarantee their environmentally positive origin, and ultimately help assist the transition to a greener future. This paper explores the varying production methods, with consideration to their environmental impact, and the implications of the use of certificates and blockchain to monitor production, trade and usage

Retromer deficiency in Tauopathy models enhances the truncation and toxicity of Tau.

Alteration of the levels, localization or post-translational processing of the microtubule associated protein Tau is associated with many neurodegenerative disorders. Here we develop adult-onset models for human Tau (hTau) toxicity in Drosophila that enable age-dependent quantitative measurement of central nervous system synapse loss and axonal degeneration, in addition to effects upon lifespan, to facilitate evaluation of factors that may contribute to Tau-dependent neurodegeneration. Using these models, we interrogate the interaction of hTau with the retromer complex, an evolutionarily conserved cargo-sorting protein assembly, whose reduced activity has been associated with both Parkinson’s and late onset Alzheimer’s disease. We reveal that reduction of retromer activity induces a potent enhancement of hTau toxicity upon synapse loss, axon retraction and lifespan through a specific increase in the production of a C-terminal truncated isoform of hTau. Our data establish a molecular and subcellular mechanism necessary and sufficient for the depletion of retromer activity to exacerbate Tau-dependent neurodegeneration.post-print2287 K

Operational considerations for hot-washing in potato crisp manufacture

As part of an overall programme aimed at reducing the acrylamide content of crisps, this paper explores the impact of hot-washing on potato slice sugar concentration during industrial scale manufacture. We investigated cold-washing as an alternative to hot-washing, hot-wash residence time and temperature to optimise sugar removal and therefore reduce the potential for high acrylamide levels after frying. Due to the variable nature of potatoes, an extensive variability study was performed to determine confidence boundaries of results. It was found that the cold-wash unit removed on average 21% of the initial sugar content. In the hot-wash the current operational residence time of 3.5 minutes at 70oC gave a sugar reduction of 27.5%, which could be increased to 48.5% if residence time is extended to 5 minutes. Hot-wash temperatures of 40oC - 60oC were found to increase glucose and fructose content and therefore the potential for acrylamide formation. A “double cold-wash” was trialled and proved to be as successful as hot-washing at 70oC for all but the highest sugar potatoes, challenging the current operational process and offering the potential for major energy savings

Fryer control strategy improvement:towards acrylamide reduction in crisp manufacture

This paper describes research efforts to improve the operation of industrial scale crisp fryers to ensure that product quality targets are exceeded. The work described was undertaken within a project whose aim is to minimise the acrylamide formation arising during processing operations. The existing fryer temperature control scheme was found to be sub-optimal from an acrylamide perspective and involved considerable operator intervention, particularly at fryer start-up. A new temperature control system was designed and implemented to overcome the shortcomings of the existing strategy. Fryer temperature and crisp moisture were regulated effectively through gas flow and dwell time modifications. Interactions between loops were compensated for and start-up was automated to reduce the impact of operator-to-operator variation. The resulting scheme was found to deliver much-improved temperature control which will lead to a resultant decrease in acrylamide formation

Cosmogenic ^(10)Be and ^(36)Cl geochronology of offset alluvial fans along the northern Death Valley fault zone: Implications for transient strain in the eastern California shear zone

The northern Death Valley fault zone (NDVFZ) has long been recognized as a major right-lateral strike-slip fault in the eastern California shear zone (ECSZ). However, its geologic slip rate has been difficult to determine. Using high-resolution digital topographic imagery and terrestrial cosmogenic nuclide dating, we present the first geochronologically determined slip rate for the NDVFZ. Our study focuses on the Red Wall Canyon alluvial fan, which exposes clean dextral offsets of seven channels. Analysis of airborne laser swath mapping data indicates ∼297 ± 9 m of right-lateral displacement on the fault system since the late Pleistocene. In situ terrestrial cosmogenic ^(10)Be and ^(36)Cl geochronology was used to date the Red Wall Canyon fan and a second, correlative fan also cut by the fault. Beryllium 10 dates from large cobbles and boulders provide a maximum age of 70 +22/−20 ka for the offset landforms. The minimum age of the alluvial fan deposits based on ^(36)Cl depth profiles is 63 ± 8 ka. Combining the offset measurement with the cosmogenic ^(10)Be date yields a geologic fault slip rate of 4.2 +1.9/−1.1 mm yr^(−1), whereas the ^(36)Cl data indicate 4.7 +0.9/−0.6 mm yr^(−1) of slip. Summing these slip rates with known rates on the Owens Valley, Hunter Mountain, and Stateline faults at similar latitudes suggests a total geologic slip rate across the northern ECSZ of ∼8.5 to 10 mm yr^(−1). This rate is commensurate with the overall geodetic rate and implies that the apparent discrepancy between geologic and geodetic data observed in the Mojave section of the ECSZ does not extend north of the Garlock fault. Although the overall geodetic rates are similar, the best estimates based on geology predict higher strain rates in the eastern part of the ECSZ than to the west, whereas the observed geodetic strain is relatively constant

Male infertility-linked point mutation disrupts the Ca2+ oscillation-inducing and PIP2 hydrolysis activity of sperm PLCζ

A male infertility-linked human PLCζ (phospholipase Cζ) mutation introduced into mouse PLCζ completely abolishes both in vitro PIP2 (phosphatidylinositol 4,5-bisphosphate) hydrolysis activity and the ability to trigger in vivo Ca2+ oscillations in mouse eggs. Wild-type PLCζ initiated a normal pattern of Ca2+ oscillations in eggs in the presence of 10-fold higher mutant PLCζ, suggesting that infertility is not mediated by a dominant-negative mechanism