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Mobile cloud storage (MCS) provides clients with convenient cloud storage service. In this paper, we propose an efficient, secure and privacy-preserving mobile cloud storage scheme, which protects the data confidentiality and privacy simultaneously, especially the access pattern. Specifically, we propose an oblivious selection and update (OSU) protocol as the underlying primitive of the proposed mobile cloud storage scheme. OSU is based on onion additively homomorphic encryption with constant encryption layers and enables the client to obliviously retrieve an encrypted data item from the cloud and update it with a fresh value by generating a small encrypted vector, which significantly reduces the client's computation as well as the communication overheads. Compared with previous works, our presented work has valuable properties, such as fine-grained data structure (small item size), lightweight client-side computation (a few of additively homomorphic operations) and constant communication overhead, which make it more suitable for MCS scenario. Moreover, by employing the "verification chunks" method, our scheme can be verifiable to resist malicious cloud. The comparison and evaluation indicate that our scheme is more efficient than existing oblivious storage solutions with the aspects of client and cloud workloads, respectively.

With the increasing number of traffic accidents and terrorist attacks by modern vehicles, vehicular digital forensics (VDF) has gained significant attention in identifying evidence from the related digital devices. Ensuring the law enforcement agency to accurately integrate various kinds of data is a crucial point to determine the facts. However, malicious attackers or semi-honest participants may undermine the digital forensic procedures. Enabling accountability and privacy-preservation while providing secure data access control in VDF is a non-trivial challenge. To mitigate this issue, in this paper, we propose a blockchain-based decentralized solution for VDF named BB-VDF, in which the accountable protocols and privacy-preserving algorithm are constructed. The desirable security properties and fine-grained data access control are achieved based on smart contract and the customized cryptographic construction. Specifically, we design a distributed key-policy attribute based encryption scheme with partially hidden access structures, named DKP-ABE-H, to realize the secure fine-grained forensics data access control. Further, a novel smart contract is designed to model the forensics procedures as a finite state machine, which guarantees accountability that each participant performs auditable cooperation under tamper-resistant and traceable transactions. Systematic security analysis and extensive experimental results show the feasibility and practicability of our proposed BB-VDF scheme.

To investigate the effect of Met kinase inhibitor BMS-777607 on proliferation and apoptosis of tongue squamous cell carcinoma cell line CAL27.The effect of BMS-777607 on proliferation of CAL27 was detected by MTT method, clone formation assay and EdU cell imaging. Morphological changes of apoptosis of CAL27 cells induced by BMS-777607 were observed by Heochst33342 staining. JC-1 staining was used to detect the changes of mitochondrial membrane potential of CAL27 cells treated with BMS-777607. Western blot was used to detect the effect of BMS-777607 on the expression of proliferation protein Akt, p-Akt and apoptosis-related proteins Bcl-2, Cleaved caspase-3, Bax and Parp in CAL27 cells. The data were analyzed using SPSS 22.0 software package.BMS-777607 inhibited proliferation and promoted apoptosis of CAL27 cells in a concentration-dependent manner（P＜0.05）. It also inhibited the expression of Bcl-2 and p-Akt and promoted the expression of Bax, Cleaved caspase-3 and Parp protein (P＜0.05).BMS-777607 can inhibit proliferation and promote apoptosis of CAL27 cells.

Ferroelectric Rashba semiconductors (FERSCs) have recently attracted intensive attention due to their giant bulk Rashba parameter, αR, which results in a locking between the spin degrees of freedom and the switchable electric polarization. However, the integration of FERSCs into microelectronic devices has provoked questions concerning whether the Rashba effect can persist when the material thickness is reduced to several nanometers. Here we find that αR can keep a large value of 2.12 eV A in the 5.0 nm thick GeTe film. The behavior of αR with thickness can be expressed by the scaling law and provides a 3D thickness limit of the bulk Rashba effect, dc = 2.1 ± 0.5 nm. Finally, we find that the thickness can modify the Berry curvature as well, which influences the polarization and consequently alters the αR. Our results give insight into understanding the factors influencing αR in FERSCs and pave a novel route for designing Rashba-type quantum materials.

Insects rely on olfaction to locate their host plants by antennae in complex chemical environments. Odorant receptor (OR) genes are thought to play a crucial role in the process. ORs function together with odorant coreceptors to determine the specificity and sensitivity of olfactory reception. The dark black chafer, Holotrichia parallela Motschulsky (Coleoptera: Scarabaeidae), is a destructive underground pest. To understand the molecular basis of H. parallela olfactory reception, an olfactory-biased expressed odorant receptor HparOR27 and HparOrco (HparOR40) were identified from antennal transcriptome analysis and prediction of the sequence structure. Tissue expression analysis showed that HparOR27 was mainly expressed in adult antennae throughout developmental stages. The functions of HparOR27 were analyzed using the Xenopus laevis oocyte expression system. HparOR27 was broadly responsive to three host plant volatiles, including hexanal, lauric acid, and tetradecane. Electroantennogram tests confirmed that three ligands were electrophysiologically active in antennae of female adults. A Y-tube olfactometer test indicated that hexanal was a repellent for adults of both sexes. Taken together, our data support the identification of odorant receptors and provide a molecular basis for eco-friendly pest control.

This paper proposes a new approach for privacy-preserving and verifiable convolutional neural network (CNN) testing, enabling a CNN model developer to convince a user of the truthful CNN performance over non-public data from multiple testers, while respecting model privacy. To balance the security and efficiency issues, three new efforts are done by appropriately integrating homomorphic encryption (HE) and zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) primitives with the CNN testing. First, a CNN model to be tested is strategically partitioned into a private part kept locally by the model developer, and a public part outsourced to an outside server. Then, the private part runs over HE-protected test data sent by a tester and transmits its outputs to the public part for accomplishing subsequent computations of the CNN testing. Second, the correctness of the above CNN testing is enforced by generating zk-SNARK based proofs, with an emphasis on optimizing proving overhead for two-dimensional (2-D) convolution operations, since the operations dominate the performance bottleneck during generating proofs. We specifically present a new quadratic matrix programs (QMPs)-based arithmetic circuit with a single multiplication gate for expressing 2-D convolution operations between multiple filters and inputs in a batch manner. Third, we aggregate multiple proofs with respect to a same CNN model but different testers' test data (i.e., different statements) into one proof, and ensure that the validity of the aggregated proof implies the validity of the original multiple proofs. Lastly, our experimental results demonstrate that our QMPs-based zk-SNARK performs nearly 13.9$\times$faster than the existing QAPs-based zk-SNARK in proving time, and 17.6$\times$faster in Setup time, for high-dimension matrix multiplication.

Dual topological insulators, simultaneously protected by time-reversal symmetry and crystalline symmetry, open great opportunities to explore different symmetry-protected metallic surface states. However, the conventional dual topological states located on different facets hinders integration into planar opto-electronic/spintronic devices. Here, we construct dual topological superlattices (TSLs) Bi