No abstract

Background/Objectives: Recently, as the fourth industrial revolution has emerged, cloud computing services have been attracting attention for efficient use of Internet-based computing resources. Among the cloud computing services, even if the data processed by the mobile device is encrypted after being stored in the server, the confidential information can be leaked. Therefore, there is a need for the key generation for data encryption and decryption.Methods/Statistical analysis: In this paper, we propose a key distribution protocol that enables mobile devices to securely encrypt and decrypt keys in an efficient manner in a cloud environment. The main purpose of the proposed protocol is to maximize the efficiency and cost reduction of key generation, which can securely transmit and receive data, in a situation where the size of data used in the cloud environment and the storage location are increasing. As a result of the performance evaluation, the proposed method improved the authentication processing time by 4.1% on average compared with the existing protocol, and the average throughput rate of the server per unit time was 6.5%. In addition, the communication delay time between the authentication server and the mobile device improved by 9.3% on average, and the authentication overhead of the server was 11.5% lower than that of the conventional method.Findings: In order to solve this problem, the proposed protocol can solve the security problem of the mobile device because it can receive the authentication through the one - way hash function and the XOR operation using the encrypted data using the session key.Improvements/Applications: In future studies, we will apply the proposed protocol to the actual environment based on the results of this study and compare it with the results obtained from the theoretical studies.

Background/Objectives: Due to the development of mobile communication technology, infrastructure construction from 4G to 5G service, which is currently being serviced, is actively under way. In particular, as the types and functions of mobile phones and IoT devices using 5G services are diversified, mutual authentication technology among multiple users is required.Methods/Statistical analysis: In this paper, we propose a multi - user authentication scheme which can efficiently mutually authenticate different types of mobile phones and IoT devices that are provided with 5G service. The proposed method minimizes the authentication delay time because it identifies the authentication security parameter δ of multiple users requesting authentication to the server as a polynomial coefficient. As a result of the performance evaluation, the proposed method showed an average improvement of 9.3% in authentication processing time and 5.5% lower overhead than the existing method. In addition, the multiuser authentication latency was improved by 6.1% on average compared with the existing scheme.Findings: The proposed scheme minimizes the user 's authentication delay time by constructing the users who simultaneously request the 5G service into a subnet and then applying the authentication security parameter δ constituting each subnet to n - bit and applying it to the polynomial coefficients. Especially, for multi - user authentication, the proposed scheme divides the authentication path into two paths (main path and secondary path) to guarantee user authentication and integrity. The proposed scheme is suitable for mobile phones and IoT devices that use low power because it generates keys without performing additional cryptographic algorithms like conventional techniques when performing multi - user authentication.Improvements/Applications: In future research, we plan to apply the proposed method to the actual environment based on the results of this study.

By the dependence on Web from popularization of internet and increasing number of users, web services capability and security problem of communication is becoming a great issue. Existing web services technology decrease the capability of web application server by limiting the number of synchronous client, decreasing the processing load and increasing average response time. The encryption process to secure communication and the early expense of handshake decrease transmission speed and server capability by increasing the calculation time for connecting. Accordingly, this paper executes an encryption procedure by elliptical encryption algorithm to satisfy secure demands, improve the overload of server for web services and get reliability and security of web server architecture and proposes an improved mobile web sever which provides better ability and the techniques for deferred processing.

Background/Objectives: As the use of big data increases in various fields, the use of social big data analysis for social media is increasing rapidly.This study proposed a method to apply text clustering for analysis by related topics of texts extracted using text mining of social big data.Methods/Statistical analysis: R was used for data collection and analysis, and social big data was collected from Twitter. The clustering model applicable to the related subject analysis of Twitter text was compared and selected and text clustering was performed. Text clustering is analyzed through a cluster dendrogram by generating a corpus, then grouping similar entities from the term-document matrix, and removing the sparse words.Findings: In this study, text clustering improves the difficulty in analyzing by word association and subject in text mining methods such as word cloud. Especially, in the text clustering model for the related topic analysis of social big data, the hierarchical clustering model based on the cosine similarity was more suitable than the non-hierarchical model for identifying which terms in the tweet have an association with each other. In addition, cluster dendrogram has been found to be effective in analyzing text contexts by grouping several groups of similar texts repeatedly in the visualization process.Improvements/Applications: This study can be used to confirm ideas and opinions of various participants by using Social Big Data, and to analyze more precisely the complex relationship between the prediction of social problems and the phenomenon.