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The largest number of cybersecurity attacks is on web applications, in which Cross-Site Scripting (XSS) is the most popular way. The code audit is the main method to avoid the damage of XSS at the source code level. However, there are numerous limits implementing manual audits and rule-based audit tools. In the age of big data, it is a new research field to assist the manual auditing through machine learning. In this paper, we propose a new way to audit the XSS vulnerability in PHP source code snippets based on a PHP code parsing tool and the machine learning algorithm. We analyzed the operation sequence of source code and built a model to acquire the information that is most closely related to the XSS attack in the data stream. The method proposed can significantly improve the recall rate of vulnerability samples. Compared with related audit methods, our method has high reusability and excellent performance. Our classification model achieved an F1 score of 0.92, a recall rate of 0.98 (vulnerable sample), and an area under curve (AUC) of 0.97 on the test dataset.

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The hydraulic driving source plays an important role in the performance of the electro-hydraulic robot. In this paper, the Lumped parameter method is used to establish the pressure-flow characteristic model of the constant pressure variable pump of a 6-DOF electro-hydraulic robot, and attain the influencing factors of the flow pulsation. The simulation model of the electro-hydraulic robot is established, which is used to study the oil property and plunger leakage characteristics of the constant pressure variable pump on the affection of the flow pulsation. The experimental results display that the elastic pulsation is the main form of the output flow pulsation of the constant pressure variable pump, and the pulsation rate will increase with the load quantity of the robot.

This paper experimentally presented the water stability of magnesium phosphate cement (MPC) modified by nano-Al2O3 (NA), nano-Fe2O3 (NF) and water glass (WG). The optimal addition of 6% NA, 2% NF and 1% WG significantly improved the water stability of MPC mortar by 86%, 101% and 96% after 28 days of water immersion, respectively. X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM) were used to analyze the water stability of MPC modified by NA, NF and WG. The results of the micrograph and composition analysis revealed that the proper amount of NA, NF or WG could fill the micro pores and improve the hydration of interior structures of MPC mortar. Thus, the microstructural compactness was satisfied to keep a good water stability of MPC mortar.

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