Biblio

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.

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.

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.

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.

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.

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.

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.