With the continuous development of Web attacks, many web applications have been suffering from various forms of security threats and network attacks. The security detection of URLs has always been the focus of Web security. Many web application resources can be accessed by simply entering an URL or clicking a link in the browser. An attacker can construct various web attacks such as SQL, XSS, and information disclosure by embedding executable code or injecting malicious code into the URL. Therefore, it is necessary to improve the reliability and security of web applications by accurately detecting malicious URLs. This paper designs a convolutional gated-recurrent-unit (GRU) neural network for the detection of malicious URLs detection based on characters as text classification features. Considering that malicious keywords are unique to URLs, a feature representation method of URLs based on malicious keywords is proposed, and a GRU is used in place of the original pooling layer to perform feature acquisition on the time dimension, resulting in high-accuracy multicategory results. The experimental results show that our proposed neural network detection model is very suitable for high-precision classification tasks. Compared with other classification models, the model accuracy rate is above 99.6%. The use of deep learning to classify URLs to identify Web visitors' intentions has important theoretical and scientific values for Web security research, providing new ideas for intelligent security detection. INDEX TERMS Gated recurrent unit (GRU), malicious URL detection, network attack, character-level embedding, convolutional neural network, neural network model.

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Synchronized Phasor Measurement Unit with CAN bus can be used to phasor acquisition and real-time dynamic monitoring of ship power system. As it is known to all, traditional CAN communication is based on event-triggered mechanism. Message transmission will be delayed when there are a lot of messages in CAN bus. This paper used TTCAN protocol to synchronize the master and slave clock nodes based on STM32 microcontrollers. A Fast Fourier transform of AD samples was been done and transferred to host computer through CAN bus which reflects the real-time running status of system well.

Abstract. The performance of hash-based Scheduling optimization algorithm for network flow cannot be bounded under the worst-case because of hash conflicts. To make up for the shortage of the above algorithm, a multiple-hash algorithm based on counting Hash Adapter, which stores the digest of flow needed to be adjusted in the Exact Stream Hash Adapter(ESHA) structure, is designed. Compared with the basic hash table, the integrity of the conversation is maintained and the query performance is improved due to the lower probability of conflict. An example is given as a validation of this method and the result data reflect the practical effect.