Relational database management system is the most popular database system. It is important to maintain data security from information leakage and data corruption. RDBMS can be attacked by an outsider or an insider. It is difficult to detect an insider attack because its patterns are constantly changing and evolving. In this paper, we propose an adaptive database intrusion detection system that can be resistant to potential insider misuse using evolutionary reinforcement learning, which combines reinforcement learning and evolutionary learning. The model (...) consists of two neural networks, an evaluation network and an action network. The action network detects the intrusion, and the evaluation network provides feedback to the detection of the action network. Evolutionary learning is effective for dynamic patterns and atypical patterns, and reinforcement learning enables online learning. Experimental results show that the performance for detecting abnormal queries improves as the proposed model learns the intrusion adaptively using Transaction Processing performance Council-E scenario-based virtual query data. The proposed method achieves the highest performance at 94.86%, and we demonstrate the usefulness of the proposed method by performing 5-fold cross-validation. (shrink)

On Buddhist doctrinal and philosophical interpretation of Sakyapa tradition.

Due to the large-scale mining of mineral resources, the surface strata in many areas have collapsed and even developed into deformation and subsidence. Based on the conventional geotechnical deformation monitoring technology, the surface deformation prediction and disaster caused by the conventional geotechnical deformation monitoring technology can be avoided. In this paper, based on GIS, combined with the analysis of surface settlement, the surface settlement, slope value, curvature deformation value, horizontal displacement, and corresponding horizontal deformation formula are comprehensively analyzed and studied. (...) In order to make the surface deformation visualization and realize the high approximation processing with the subsidence area, this paper innovatively introduces the 3D visualization settlement data analysis and realizes the calculation result analysis and corresponding retrieval multiple visualization in the subsidence area depth prediction process. On this basis, the prediction data of subsidence area can be optimized and analyzed so as to master the efficient and accurate law of surface deformation. In the experimental part, a mine is taken as the experimental object, and the 3D visual monitoring processing is carried out. In this paper, the main method to prevent electromagnetic leakage of the computer system is the source suppression method. The source suppression method solves the problem fundamentally by reducing or eliminating the emission of computer electromagnetic leakage source. In the actual experiment, the effect of this method is very effective. The experimental results show that the prediction results and corresponding early warning accuracy of the system are significantly improved compared with the traditional scheme, which provides practical significance for disaster prevention and corresponding environmental impact assessment. (shrink)