With the rapid development of cloud computing, outsourcing massive data and complex deep learning model to cloud servers (CSs) has become a popular trend, which also brings some security problems. One is that the model stored in the CSs may be corrupted, leading to incorrect inference and training results. The other is that the privacy of outsourced data and model may be compromised. However, existing privacy-preserving and verifiable inference schemes suffer from low detection probability, high communication overhead and substantial computational time. To solve the above problems, we propose a privacy-preserving and verifiable scheme for convolutional neural network inference and training in cloud computing. In our scheme, the model owner generates the authenticators for model parameters before uploading the model to CSs. In the phase of model integrity verification, model owner and user can utilize these authenticators to check model integrity with high detection probability. Furthermore, we design a set of privacy-preserving protocols based on replicated secret sharing for both the inference and training phases, significantly reducing communication overhead and computational time. Through security analysis, we demonstrate that our scheme is secure. Experimental evaluations show that the proposed scheme outperforms existing schemes in privacy-preserving inference and model integrity verification.

The uniform Turán density πu(F) of a (3-uniform) hypergraph F is the supremum of d for which there are infinitely many F-free hypergraphs with the property that every induced subhypergraph of H on a linearly sized vertex set has edge density at least d. Determining πu(F) for given hypergraphs F was suggested by Erdős and Sós in the 1980s. However, there are very few hypergraphs whose uniform Turán density has been determined. In this paper, we are the first to establish a verifiable condition for hypergraphs F with πu(F)=1/4. In particular, currently known hypergraphs whose uniform Turán density is 1/4, such as K4(3)- studied in Glebov et al. (Israel J Math 211:349–366, 2016) and Reiher et al. (J Eur Math Soc 20:1139–1159, 2018), and F5⋆ studied in Chen and Schülke (Beyond the broken tetrahedron, 2022, arXiv:2211.12747), satisfy this condition. Moreover, we also identify some new hypergraphs whose uniform Turán density is also 1/4.

A t-out-of-n threshold ring signature allows t parties to jointly sign a message on behalf of n parties without revealing the identities of the signers. In this paper, we introduce a new generic construction for threshold ring signature, called GC-TRS, which can be built on top of a selection on identification schemes, commitment schemes, and a new primitive called t-out-of-n proof protocol which is a special type of zero-knowledge proof. In general, our design enables a group of t signers to first generate an aggregated signature by interacting with each other; then they are able to compute a t-out-of-n proof to convince the verifier that the aggregated signature is indeed produced by t individuals among a particular set. The signature is succinct, as it contains only one aggregated signature and one proof in the final signature. We define all the properties required for the building blocks to capture the security of the GC-TRS and provide a detailed security proof. Furthermore, we propose two lattice-based instantiations for the GC-TRS, named LTRS and CTRS, respectively. Notably, the CTRS scheme is the first scheme that has a logarithmic signature size relative to the ring size. Additionally, during the instantiation process, we construct two t-out-of-n proof protocols, which may be of independent interest.

Silicon heterojunction (SHJ) solar cells have reached high power conversion efficiency owing to their effective passivating contact structures. Improvements in the optoelectronic properties of these contacts can enable higher device efficiency, thus further consolidating the commercial potential of SHJ technology. Here we increase the efficiency of back junction SHJ solar cells with improved back contacts consisting of p-type doped nanocrystalline silicon and a transparent conductive oxide with a low sheet resistance. The electrical properties of the hole-selective contact are analysed and compared with a p-type doped amorphous silicon contact. We demonstrate improvement in the charge carrier transport and a low contact resistivity (<5 mΩ cm²). Eventually, we report a series of certified power conversion efficiencies of up to 26.81% and fill factors up to 86.59% on industry-grade silicon wafers (274 cm², M6 size).