With the rapid development of China's economy and the continuous improvement of technological innovation ability, efficient organization and classification information is the basis of providing personalized industry management and tracking analysis. According to the characteristics of industry infor...

Keyword extraction has a great impact on text processing, and the accuracy and fluency of keyword recognition are the keys to the task. In order to effectively solve the problems such as inaccurate word division, mismatch between keywords and text topics, and multi-language mixing in the process of ...

With the rapid development of online social media, the analysis of the dissemination mode of public opinion information has become a research hotspot.Aiming at the problem of low classification accuracy of small sample data multi-path generation in the classification task of the network public opini...

As the most effective method of vulnerability mining at present, fuzzy testing not only is more capable of dealing with complex programs than other vulnerability mining techniques, but also has strong scalability. In the fuzzy testing with a large number of data, the input sample set has the problem...

A low redundancy feature selection method for Android malware detection is proposed to solve the problem of feature redundancy caused by excessive attention to features with the same frequency distribution between classes. First, the method selects features with frequency distribution bias by Mann-W...

The traffic classification of Internet of things (IoT) devices is very important to the management of cyberspace assets. The classification technology based on statistical identification is a hot spot in current academic research. The previous algorithms were mainly based on the flow information to ...

Recently, Internet of things (IoT) malware emerges in large numbers and attacks IoT devices in cyberspace. However, the family characteristics of IoT malwares are not obvious due to the open-source problem, a more fine-grained malware classification method is needed to solve the problems of advanced...

Due to the variety of data types and desensitization demand in different scenarios, traditional data masking methods cannot meet the user privacy protection requirements in the environment of big data. How to realize the accurate pointing and efficient desensitization of heterogeneous big data for d...

Malicious codes poses serious threats to network and information security. How to detect malware rapidly and how to eliminate and reduce the hazard caused by malware are important research topics. The paper presents a method to get dynamic features of malware using dynamic information and heterogene...

Encrypting the documents before uploading them to the untrusted removable server is one of the ultimate solutions to protect the user privacy. As different encryption schemes give different ranking results, finding the order preserving encryption scheme that gives the best ranking result is the key ...

Currently, the number of mobile phone users in China has reached 1.59 billion. Under the huge population base, the telecom big data characteristics reflect the characteristics of crowd activities to a certain extent, which can reflect the development status of specific regions. The application of sp...

Malicious code clone detection has become an effective way to analyze malicious code homology and advanced persistent threat (APT) attacks. In this paper, we collect samples of different APT organizations from public threat intelligence, and propose a deep learning based malicious code clone detecti...

Cipher suite is the cornerstone of transport layer security (TLS) to realize secure communication, which includes asymmetric cipher algorithm, symmetric cipher algorithm and message digest algorithm, among which symmetric cipher algorithm is used for data encryption in actual communication. Through ...

Weibo contains a large number of information reflecting users' likes and dislikes, which is important for popular trend judgment, precision marketing, public opinion monitoring, etc. However, the existing methods tend to focus on the classification of Weibo sentiment. In order to solve the problem o...

With the popularization of smart grids and the development of big data technology, more and more attention has been paid to the analysis of users' electricity consumption behavior through electricity consumption data. The existing energy decomposition methods cannot meet the high requirements for re...

Due to the limited computing and storage resources, the smart grid embedded devices cannot deal with the network attacks effectively and the security assessment method is weak. In order to solve these problems, a dynamic network attack behavior evaluation method for smart grid embedded devices is pr...

Based on the research and analysis of machine learning technology to detect malicious code, a local interpretable model-agnostic explanations (LIME)-based black-box adversarial examples generation method is proposed to generate adversarial samples for any black-box malicious code classifier and bypa...

During the generation of black-box adversarial examples, an attack pair is usually specified, including a source example and a target example. The purpose is to let the generated adversarial example only have little norm difference from the source example, but it is recognized by the classifier as t...

The emergence of malware variants poses a great threat to network security. In malware family classification methods based on assembly instructions, the semantics of operands are closely related to the operating environment and difficult to extract, which leads to the lack of instruction semantics a...

The popularization of intelligence puts forward new requirements for image editing. As a way of transmitting information in the form of images, posters play an important role in daily life and work management. But the production of posters requires multi-element image synthesis. However, there is a ...