Dafang Zhang

TL;DR: This work proposes a novel design to estimate the dynamic Laplacian matrix of the graph with above two components based on the theoretical derivation, and creatively incorporates tensor decomposition into the deep learning framework.

TL;DR: Experimental results show that the proposed scheme improves the repair rate of multinode data by 9% and data storage rate increased by 8.6%, indicating to be promising with good security and real-time performance.

TL;DR: A fast deep-reinforcement-learning (DRL)-based detection algorithm for virtual IP watermarks is proposed by combining the technologies of mapping function and DRL to preprocess the ownership information of the IP circuit resource.

TL;DR: A homomorphic encryption-based Blockchain for circuit copyright protection that effectively addresses the issues in the protection of circuit copyright transactions, such as low security of private data, low efficiency in transaction data storage, cooperation and supervision.

TL;DR: This paper directly models the monitoring data in each time slot as a 2-D matrix, and detects anomalies in the new time slot based on bilateral principal component analysis (B-PCA), the first work that exploits 2- D PCA for anomaly detection.