Digital rights management (DRM) applications are usually confronted with threats like key extraction, code lifting, and illegal distribution. White-box cryptography aims at protecting software implementations of cryptographic algorithms and can be employed into DRM applications to provide security. A general DRM solution based on white-box cryptography was proposed to address the three threats mentioned above. The method is to construct a general perturbation-enabled white-box compiler for lookup-table based white-box block ciphers, such that the white-box program generated by this compiler provides traceability along with resistance against key extraction and code lifting. To get a traceable white-box program, the idea of hiding a slight perturbation in the lookup-table was employed, aiming at perturbing its decryption functionality, so that each user can be identified. Security analysis and experimental results show that the proposed DRM solution is secure and practical.

At present, there is an urgent need for blockchain interoperability technology to realize interconnection between various blockchains, data communication and value transfer between blockchains, so as to break the ‘ value silo’ phenomenon of each blockchain. Firstly, it lists what people understand about the concept of interoperability. Secondly, it gives the key technical issues of cross-chain, including cross-chain mechanism, interoperability, eventual consistency, and universality. Then, the implementation of each cross-chain key technology is analyzed, including Hash-locking, two-way peg, notary schemes, relay chain scheme, cross-chain protocol, and global identity system. Immediately after that, five typical cross-chain systems are introduced and comparative analysis is made. In addition, two examples of cross-chain programmability and their analysis are given. Finally, the current state of cross-chain technology is summarized from two aspects: key technology implementation and cross-chain application enforcement. The cross-chain technology as a whole has formed a centralized fixed mechanism, as well as a trend of modular design, and some of the solutions to mature applications were established in the relevant standards organizations, and the cross-chain technology architecture tends to be unified, which is expected to accelerate the evolution of the open cross-chain network that supports the real needs of the interconnection of all chains.

As a way of training a single hidden layer feedforward network (SLFN),extreme learning machine (ELM) is rapidly becoming popular due to its efficiency. However, ELM tends to overfitting, which makes the model sensitive to noise and outliers. To solve this problem, L2,1-norm is introduced to ELM and an L2,1-norm robust regularized ELM (L2,1-RRELM) was proposed. L2,1-RRELM gives constant penalties to outliers to reduce their adverse effects by replacing least square loss function with a non-convex loss function. In light of the non-convex feature of L2,1-RRELM, the concave-convex procedure (CCCP) is applied to solve its model. The convergence of L2,1-RRELM is also given to show its robustness. In order to further verify the effectiveness of L2,1-RRELM, it is compared with the three popular extreme learning algorithms based on the artificial dataset and University of California Irvine (UCI) datasets. And each algorithm in different noise environments is tested with two evaluation criterions root mean square error (RMSE) and fitness. The results of the simulation indicate that L2,1-RRELM has smaller RMSE and greater fitness under different noise settings. Numerical analysis shows that L2,1-RRELM has better generalization performance, stronger robustness, and higher anti-noise ability and fitness.

This paper proposes a novel high-power supply rejection ratio (high-PSRR) high-order curvature-compensated CMOS bandgap voltage reference (BGR) in SMIC 0.18 μm CMOS process. Three kinds of current are added to a conventional BGR in order to improve the temperature drift within wider temperature range, which include a piecewise-curvature- corrected current in high temperature range, a piecewise-curvature-corrected current in low temperature range and a proportional-to-absolute-temperature current. The high-PSRR characteristic of the proposed BGR is achieved by adopting the technique of pre-regulator. Simulation results shows that the temperature coefficient of the proposed BGR with pre-regulator is /°C from 55 °C to 125 °C with a 1.8 V power supply voltage. The proposed BGR with pre-regulator achieves PSRR of 123.51 dB, 123.52 dB, 88.5 dB and 50.23 dB at 1 Hz, 100 Hz, 100 kHz and 1 MHz respectively.