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Jiang, Hua.  2021.  Application and Research of Intelligent Security System Based on NFC and Cloud Computing Technology. 2021 20th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES). :200–202.
With the rapid development of urbanization, community security and public security have become an important social issue. As conventional patrol methods can not effectively ensure effective supervision, this paper studies the application of NFC (Near Field Communication) technology in intelligent security system, designs and constructs a set of intelligent security system suitable for public security patrol or security patrol combined with current cloud service technology. The system can not only solve the digital problem of patrol supervision in the current public security, but also greatly improve the efficiency of security and improve the service quality of the industry through the application of intelligent technology.
Zhang, Guangxin, Zhao, Liying, Qiao, Dongliang, Shang, Ziwen, Huang, Rui.  2021.  Design of transmission line safety early warning system based on big data variable analysis. 2021 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS). :90–93.
In order to improve the accuracy and efficiency of transmission line safety early warning, a transmission line safety early warning system based on big data variable analysis is proposed. Firstly, the overall architecture of the system is designed under the B / S architecture. Secondly, in the hardware part of the system, the security data real-time monitoring module, data transmission module and security warning module are designed to meet the functional requirements of the system. Finally, in the system software design part, the big data variable analysis method is used to calculate the hidden danger of transmission line safety, so as to improve the effectiveness of transmission safety early warning. The experimental results show that, compared with the traditional security early warning system, the early warning accuracy and efficiency of the designed system are significantly improved, which can ensure the safe operation of the transmission line.
Ma, Yingjue, Ni, Hui-jun, Li, Yanping.  2021.  Information Security Practice of Intelligent Knowledge Ecological Communities with Cloud Computing. 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE). :242–245.
With powerful ability to organize, retrieve and share information, cloud computing technology has effectively improved the development of intelligent learning ecological Communities. The study finds development create a security atmosphere with all homomorphic encryption technology, virtualization technology to prevent the leakage and loss of information data. The result provided a helpful guideline to build a security environment for intelligent ecological communities.
Xue, Bi.  2021.  Information Fusion and Intelligent Management of Industrial Internet of Things under the Background of Big Data. 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). :68–71.
This paper summarizes the types and contents of enterprise big data information, analyzes the demand and characteristics of enterprise shared data information based on the Internet of things, and analyzes the current situation of enterprise big data fusion at home and abroad. Firstly, using the idea of the Internet of things for reference, the intelligent sensor is used as the key component of data acquisition, and the multi energy data acquisition technology is discussed. Then the data information of entity enterprises is taken as the research object and a low energy consumption transmission method based on data fusion mechanism for industrial ubiquitous Internet of things is proposed. Finally, a network monitoring and data fusion platform for the industrial Internet of things is implemented. The monitoring node networking and platform usability test are also performed. It is proved that the scheme can achieve multi parameter, real-time, high reliable network intelligent management.
Sun, Yue, Dong, Bin, Chen, Wei, Xu, Xiaotian, Si, Guanlin, Jing, Sen.  2021.  Research on Security Evaluation Technology of Intelligent Video Terminal. 2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC). :339–342.
The application of intelligent video terminal has spread in all aspects of production and life, such as urban transportation, enterprises, hospitals, banks, and families. In recent years, intelligent video terminals, video recorders and other video monitoring system components are frequently exposed to high risks of security vulnerabilities, which is likely to threaten the privacy of users and data security. Therefore, it is necessary to strengthen the security research and testing of intelligent video terminals, and formulate reinforcement and protection strategies based on the evaluation results, in order to ensure the confidentiality, integrity and availability of data collected and transmitted by intelligent video terminals.
Chen, Lin, Qiu, Huijun, Kuang, Xiaoyun, Xu, Aidong, Yang, Yiwei.  2021.  Intelligent Data Security Threat Discovery Model Based on Grid Data. 2021 6th International Conference on Image, Vision and Computing (ICIVC). :458–463.
With the rapid construction and popularization of smart grid, the security of data in smart grid has become the basis for the safe and stable operation of smart grid. This paper proposes a data security threat discovery model for smart grid. Based on the prediction data analysis method, combined with migration learning technology, it analyzes different data, uses data matching process to classify the losses, and accurately predicts the analysis results, finds the security risks in the data, and prevents the illegal acquisition of data. The reinforcement learning and training process of this method distinguish the effective authentication and illegal access to data.
Kong, Hongshan, Tang, Jun.  2021.  Agent-based security protection model of secret-related carrier intelligent management and control. 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA). 2:301–304.
Secret-related carrier intelligent management and control system uses the Internet of Things and artificial intelligence to solve the transformation of secret-related carrier management and control from manual operation to automatic detection, precise monitoring, and intelligent decision-making, and use technical means to resolve security risks. However, the coexistence of multiple heterogeneous networks will lead to various network security problems in the secret carrier intelligent management and control. Aiming at the actual requirements of the intelligent management and control of secret-related carriers, this paper proposes a system structure including device domain, network domain, platform domain and user domain, and conducts a detailed system security analysis, and introduces intelligent agent technology, and proposes a distributed system. The hierarchical system structure of the secret-related carrier intelligent management and control security protection model has good robustness and portability.
Jia, Xianfeng, Liu, Tianyu, Sun, Chunhui, Wu, Zhi.  2021.  Analysis on the Application of Cryptographic Technology in the Communication Security of Intelligent Networked Vehicles. 2021 6th International Conference on Automation, Control and Robotics Engineering (CACRE). :423–427.

Intelligent networked vehicles are rapidly developing in intelligence and networking. The communication architecture is becoming more complex, external interfaces are richer, and data types are more complex. Different from the information security of the traditional Internet of Things, the scenarios that need to be met for the security of the Internet of Vehicles are more diverse and the security needs to be more stable. Based on the security technology of traditional Internet of Things, password application is the main protection method to ensure the privacy and non-repudiation of data communication. This article mainly elaborates the application of security protection methods using password-related protection technologies in car-side scenarios and summarizes the security protection recommendations of contemporary connected vehicles in combination with the secure communication architecture of the Internet of Vehicles.

Yang, Ruxia, Gao, Xianzhou, Gao, Peng.  2021.  Research on Intelligent Recognition and Tracking Technology of Sensitive Data for Electric Power Big Data. 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). :229–234.
Current power sensitive data security protection adopts classification and grading protection. Company classification and grading are mainly in formulating specifications. Data classification and grading processing is carried out manually, which is heavy and time-consuming, while traditional data identification mainly relies on rules for data identification, the level of automation and intelligence is low, and there are many problems in recognition accuracy. Data classification and classification is the basis of data security protection. Sensitive data identification is the key to data classification and classification, and it is also the first step to achieve accurate data security protection. This paper proposes an intelligent identification and tracking technology of sensitive data for electric power big data, which can improve the ability of data classification and classification, help the realization of data classification and classification, and provide support for the accurate implementation of data security capabilities.
Imtiaz, Sayem Mohammad, Sultana, Kazi Zakia, Varde, Aparna S..  2021.  Mining Learner-friendly Security Patterns from Huge Published Histories of Software Applications for an Intelligent Tutoring System in Secure Coding. 2021 IEEE International Conference on Big Data (Big Data). :4869–4876.

Security patterns are proven solutions to recurring problems in software development. The growing importance of secure software development has introduced diverse research efforts on security patterns that mostly focused on classification schemes, evolution and evaluation of the patterns. Despite a huge mature history of research and popularity among researchers, security patterns have not fully penetrated software development practices. Besides, software security education has not been benefited by these patterns though a commonly stated motivation is the dissemination of expert knowledge and experience. This is because the patterns lack a simple embodiment to help students learn about vulnerable code, and to guide new developers on secure coding. In order to address this problem, we propose to conduct intelligent data mining in the context of software engineering to discover learner-friendly software security patterns. Our proposed model entails knowledge discovery from large scale published real-world vulnerability histories in software applications. We harness association rule mining for frequent pattern discovery to mine easily comprehensible and explainable learner-friendly rules, mainly of the type "flaw implies fix" and "attack type implies flaw", so as to enhance training in secure coding which in turn would augment secure software development. We propose to build a learner-friendly intelligent tutoring system (ITS) based on the newly discovered security patterns and rules explored. We present our proposed model based on association rule mining in secure software development with the goal of building this ITS. Our proposed model and prototype experiments are discussed in this paper along with challenges and ongoing work.

Guo, Jiansheng, Qi, Liang, Suo, Jiao.  2021.  Research on Data Classification of Intelligent Connected Vehicles Based on Scenarios. 2021 International Conference on E-Commerce and E-Management (ICECEM). :153–158.
The intelligent connected vehicle industry has entered a period of opportunity, industry data is accumulating rapidly, and the formulation of industry standards to regulate big data management and application is imminent. As the basis of data security, data classification has received unprecedented attention. By combing through the research and development status of data classification in various industries, this article combines industry characteristics and re-examines the framework of industry data classification from the aspects of information security and data assetization, and tries to find the balance point between data security and data value. The intelligent networked automobile industry provides support for big data applications, this article combines the characteristics of the connected vehicle industry, re-examines the data characteristics of the intelligent connected vehicle industry from the 2 aspects as information security and data assetization, and eventually proposes a scene-based hierarchical framework. The framework includes the complete classification process, model, and quantifiable parameters, which provides a solution and theoretical endorsement for the construction of a big data automatic classification system for the intelligent connected vehicle industry and safe data open applications.
Zhang, Wenrui.  2020.  Application of Attention Model Hybrid Guiding based on Artificial Intelligence in the Course of Intelligent Architecture History. 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS). :59—62.
Application of the attention model hybrid building based on the artificial intelligence in the course of the intelligent architecture history is studied in this article. A Hadoop distributed architecture using big data processing technology which combines basic building information with the building energy consumption data for the data mining research methods, and conduct a preliminary design of a Hadoop-based public building energy consumption data mining system. The principles of the proposed model were summarized. At first, the intelligent firewall processes the decision data faster, when the harmful information invades. The intelligent firewall can monitor and also intercept the harmful information in a timelier manner. Secondly, develop a problem data processing plan, delete and identify different types of problem data, and supplement the deleted problem data according to the rules obtained by data mining. The experimental results have reflected the efficiency of the proposed model.
Liu, Donglan, Wang, Rui, Zhang, Hao, Ma, Lei, Liu, Xin, Huang, Hua, Chang, Yingxian.  2020.  Research on Data Security Protection Method Based on Big Data Technology. 2020 12th International Conference on Communication Software and Networks (ICCSN). :79—83.
The construction of power Internet of things is an important development direction of power grid enterprises in the future. Big data not only brings economic and social benefits to the power system industry, but also brings many information security problems. Therefore, in the case of accelerating the construction of ubiquitous electric Internet of things, it is urgent to standardize the data security protection in the ubiquitous electric Internet of things environment. By analyzing the characteristics of big data in power system, this paper discusses the security risks faced by big data in power system. Finally, we propose some methods of data security protection based on the defects of big data security in current power system. By building a data security intelligent management and control platform, it can automatically discover and identify the types and levels of data assets, and build a classification and grading information base of dynamic data assets. And through the detection and identification of data labels and data content characteristics, tracking the use of data flow process. So as to realize the monitoring of data security state. By protecting sensitive data against leakage based on the whole life cycle of data, the big data security of power grid informatization can be effectively guaranteed and the safety immunity of power information system can be improved.
Solomon Doss, J. Kingsleen, Kamalakkannan, S..  2020.  IoT System Accomplishment using BlockChain in Validating and Data Security with Cloud. 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). :60—64.
In a block channel IoT system, sensitive details can be leaked by means of the proof of work or address check, as data or application Validation data is applied on the blockchain. In this, the zero-knowledge evidence is applied to a smart metering system to show how to improve the anonymity of the blockchain for privacy safety without disclosing information as a public key. Within this article, a blockchain has been implemented to deter security risks such as data counterfeiting by utilizing intelligent meters. Zero-Knowledge Proof, an anonymity blockchain technology, has been implemented through block inquiry to prevent threats to security like personal information infringement. It was suggested that intelligent contracts would be used to avoid falsification of intelligent meter data and abuse of personal details.
Asyaev, G. D., Antyasov, I. S..  2020.  Model for Providing Information Security of APCS Based on Predictive Maintenance Technology. 2020 Global Smart Industry Conference (GloSIC). :287—290.
In article the basic criteria of quality of work of the automated control system of technological process (APCS) are considered, the analysis of critical moments and level of information safety of APCS is spent. The model of maintenance of information safety of APCS on the basis of technology of predictive maintenance with application of intellectual methods of data processing is offered. The model allows to generate the list of actions at detection of new kinds of the threats connected with destructive influences on object, proceeding from acceptability of predicted consequences of work of APCS. In article with use of the system analysis the complex model of the technical object of automation is developed, allowing to estimate consequences from realization of threats of information safety at various system levels of APCS.
He, Kexun, Qin, Kongjian, Wang, Changyuan, Fang, Xiyu.  2020.  Research on Cyber Security Test Method for GNSS of Intelligent Connected Vehicle. 2020 International Conference on Computer Information and Big Data Applications (CIBDA). :200—203.
Intelligent connected vehicle cyber security has attracted widespread attention this year. The safety of GNSS information is related to the safety of cars and has become a key technology. This paper researches the cyber security characteristics of intelligent connected vehicle navigation and positioning by analyzing the signal receiving mode of navigation and positioning on the vehicle terminal. The article expounds the principles of deceiving and interfering cyber security that lead to the safety of GNSS information. This paper studies the key causes of cyber security. Based on key causes, the article constructs a GNSS cyber security test method by combining a navigation signal simulator and an interference signal generator. The results shows that the method can realize the security test of the GNSS information of the vehicle terminal. This method provides a test method for the navigation terminal defense cyber security capability for a vehicle terminal, and fills a gap in the industry for the vehicle terminal information security test.
Maalla, Allam.  2020.  Research on Data Transmission Security Architecture Design and Process. 2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA). 1:1195—1199.
With the development of business, management companies are currently facing a series of problems and challenges in terms of resource allocation and task management. In terms of the technical route, this research will use cloud services to implement the public honesty system, and carry out secondary development and interface development on this basis, the architecture design and the formulation of the process are realized for various types, relying on the support of the knowledge base and case library, through the system intelligent configuration corresponding work instructions, safety work instructions, case references and other reference information to the existing work plan to provide managers Reference; managers can configure and adjust the work content by themselves through specific requirements to efficiently and flexibly adapt to the work content.
Huang, Zhicai, Zhu, Huiqing.  2020.  Blockchain-based Data Security Management Mechanism for Power Terminals. 2020 International Wireless Communications and Mobile Computing (IWCMC). :191—194.
In order to solve the problem of data leakage and tampering in end-to-end power data security management, this paper proposes a Blockchain-based power terminal data security management model, which includes power terminals and Blockchain nodes. Among them, the power terminal is responsible for the collection of front-end substation data; the Blockchain node is responsible for data verification and data storage. Secondly, the data security management mechanism of power terminal based on Blockchain is proposed, including data aggregation, data encryption and transmission, signature verification for single Blockchain, aggregation signature for main Blockchain nodes, and intelligent contract storage. Finally, by applying the mechanism to the data storage process and data request process analysis, the data management mechanism proposed in this paper has a good application effect.
Xu, Hui, Zhang, Wei, Gao, Man, Chen, Hongwei.  2020.  Clustering Analysis for Big Data in Network Security Domain Using a Spark-Based Method. 2020 IEEE 5th International Symposium on Smart and Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS). :1—4.
Considering the problem of network security under the background of big data, the clustering analysis algorithms can be utilized to improve the correctness of network intrusion detection models for security management. As a kind of iterative clustering analysis algorithm, K-means algorithm is not only simple but also efficient, so it is widely used. However, the traditional K-means algorithm cannot well solve the network security problem when facing big data due to its high complexity and limited processing ability. In this case, this paper proposes to optimize the traditional K-means algorithm based on the Spark platform and deploy the optimized clustering analysis algorithm in the distributed architecture, so as to improve the efficiency of clustering algorithm for network intrusion detection in big data environment. The experimental result shows that, compared with the traditional K-means algorithm, the efficiency of the optimized K-means algorithm using a Spark-based method is significantly improved in the running time.
Sasubilli, S. M., Dubey, A. K., Kumar, A..  2020.  Hybrid security analysis based on intelligent adaptive learning in Big Data. 2020 International Conference on Advances in Computing and Communication Engineering (ICACCE). :1—5.

Big data provides a way to handle and analyze large amount of data or complex set. It provides a systematic extraction also. In this paper a hybrid security analysis based on intelligent adaptive learning in big data has been discussed with the current trends. This paper also explores the possibility of cloud computing collaboration with big data. The advantages along with the impact for the overall platform evaluation has been discussed with the traditional trends. It has been useful in the analysis and the exploration of future research. This discussion also covers the computational variability and the connotation in terms of data reliability, availability and management in big data with data security aspects.

Zhang, Z., Wang, F., Zhong, C., Ma, H..  2020.  Grid Terminal Data Security Management Mechanism Based On Master-Slave Blockchain. 2020 5th International Conference on Computer and Communication Systems (ICCCS). :67—70.

In order to design an end-to-end data security preservation mechanism, this paper first proposes a grid terminal data security management model based on master-slave Blockchain, including grid terminal, slave Blockchain, and main Blockchain. Among them, the grid terminal mainly completes data generation and data release, the receiving of data and the distributed signature of data are mainly completed from the slave Blockchain, and the main Blockchain mainly completes the intelligent storage of data. Secondly, the data security management mechanism of grid terminal based on master-slave Blockchain is designed, including data distribution process design, data receiving process design, data distributed signature design and data intelligent storage process design. Finally, taking the identity registration and data storage process of the grid terminal as an example, the workflow of the data security management mechanism of the grid terminal based on the master-slave Blockchain is described in detail.

Bao, L., Wu, S., Yu, S., Huang, J..  2020.  Client-side Security Assessment and Security Protection Scheme for Smart TV Network. 2020 IEEE 6th International Conference on Computer and Communications (ICCC). :573—578.

TV networks are no longer just closed networks. They are increasingly carrying Internet services, integrating and interoperating with home IoT and the Internet. In addition, client devices are becoming intelligent. At the same time, they are facing more security risks. Security incidents such as attacks on TV systems are commonplace, and there are many incidents that cause negative effects. The security protection of TV networks mainly adopts security protection schemes similar to other networks, such as constructing a security perimeter; there are few security researches specifically carried out for client-side devices. This paper focuses on the mainstream architecture of the integration of HFC TV network and the Internet, and conducts a comprehensive security test and analysis for client-side devices including EOC cable bridge gateways and smart TV Set-Top-BoX. Results show that the TV network client devices have severe vulnerabilities such as command injection and system debugging interfaces. Attackers can obtain the system control of TV clients without authorization. In response to the results, we put forward systematic suggestions on the client security protection of smart TV networks in current days.

Jinan, S., Kefeng, P., Xuefeng, C., Junfu, Z..  2017.  Security Patterns from Intelligent Data: A Map of Software Vulnerability Analysis. 2017 ieee 3rd international conference on big data security on cloud (bigdatasecurity), ieee international conference on high performance and smart computing (hpsc), and ieee international conference on intelligent data and security (ids). :18–25.

A significant milestone is reached when the field of software vulnerability research matures to a point warranting related security patterns represented by intelligent data. A substantial research material of empirical findings, distinctive taxonomy, theoretical models, and a set of novel or adapted detection methods justify a unifying research map. The growth interest in software vulnerability is evident from a large number of works done during the last several decades. This article briefly reviews research works in vulnerability enumeration, taxonomy, models and detection methods from the perspective of intelligent data processing and analysis. This article also draws the map which associated with specific characteristics and challenges of vulnerability research, such as vulnerability patterns representation and problem-solving strategies.