• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.358-368
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• 2022

Social media is a window for everyone, individuals, communities, and companies to spread ideas and promote trends and products. With these opportunities, challenges and problems related to security, privacy and rights arose. Also, the data accumulated from social media has become a fertile source for many analytics, inference, and experimentation with new technologies in the field of data science. In this chapter, emphasis will be given to methods of trend analysis, especially ensemble learning methods. Ensemble learning methods embrace the concept of cooperation between different learning methods rather than competition between them. Therefore, in this chapter, we will discuss the most important trends in ensemble learning and their applications in analysing social media data and anticipating the most important future trends.

• Informatization Policy
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• v.23 no.1
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• pp.3-19
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• 2016

The purpose of the study is to analyze the existing literature and to suggest future research directions in the big data security area. This study identifies 62 research articles and analyses their publication year, publication media, general research approach, specific research method, and research topic. According to the results of the analyses, big data security research is at its intial stage in which non-empirical studies and research dealing with technical issues are dominant. From the research topic perspective, the area demonstrates the signs of initial research stage in which proportion of the macro studies dealing with overall issues is far higher than the micro ones covering specific implementation methods and sectoral issues. A few promising topics for future research include overarching framework on big data security, big data security methods for different industries, and government policies on big data security. Currently, the big data security area does not have sufficient research results. In the future, studies covering various topics in big data security from multiple perspectives are anticipated.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.248-252
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• 2012

The sensor network standard DASH7 was proposed to improve transmission quality and low power communication. Specifications for the standard are currently being developed, so the security specification has not been firmly implemented. However, without a security specification, a network cannot work due to threats from malicious users. Thus we must ensure confidentiality and authentication of data packets by using a cryptography method. To contribute to the DASH7 security specification, this paper shows the implementation results of network and data link layer security by using advanced encryption standard (AES) counter with CBC-MAC (CCM) over CC430 sensor nodes.

• Journal of Information Technology Applications and Management
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• v.16 no.2
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• pp.23-43
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• 2009

For reliability and confidentiality of information security systems, the security engineering methodologies are accepted in many organizations. To improve the effectiveness of security engineering, this paper suggests a security methodology ISEM, which considers both product assurance and production processes, takes advantages in terms of quality and cost. To verify the effectiveness of ISEM, this paper introduces the concepts of quality loss, and compares the development costs and quality losses between ISEM and CC through the development of VPN system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.5
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• pp.831-847
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• 2013

The various types of data are being created in large quantities resulting from the spread of social media and the mobile popularization. Many companies want to obtain valuable business information through the analysis of these large data. As a result, it is a trend to integrate the big data technologies into the company work. Especially, Hadoop is regarded as the most representative big data technology due to its terabytes of storage capacity, inexpensive construction cost, and fast data processing speed. However, the authentication token system of Hadoop Distributed File System(HDFS) for the user authentication is currently vulnerable to the replay attack and the datanode hacking attack. This can cause that the company secrets or the personal information of customers on HDFS are exposed. In this paper, we analyze the possible security threats to HDFS when tokens or datanodes are exposed to the attackers. Finally, we propose the secure authentication protocol in HDFS based on hash chain.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.382-389
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• 2018

Recently cyber attacks can cause serious damage on various information systems. Log data analysis would be able to resolve this problem. Security log analysis system allows to cope with security risk properly by collecting, storing, and analyzing log data information. In this paper, a security log analysis system is designed and implemented in order to analyze security log data using the Logstash in the Elasticsearch, a distributed search engine which enables to collect and process various types of log data. The Kibana, an open source data visualization plugin for Elasticsearch, is used to generate log statistics and search report, and visualize the results. The performance of Elasticsearch-based security log analysis system is compared to the existing log analysis system which uses the Flume log collector, Flume HDFS sink and HBase. The experimental results show that the proposed system tremendously reduces both database query processing time and log data analysis time compared to the existing Hadoop-based log analysis system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3826-3851
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• 2016

With traditional data storage solutions becoming too expensive and cumbersome to support Big Data processing, enterprises are now starting to outsource their data requirements to third parties, such as cloud service providers. However, this outsourced initiative introduces a number of security and privacy concerns. In this paper, homomorphic encryption is suggested as a mechanism to protect the confidentiality and privacy of outsourced data, while at the same time allowing third parties to perform computation on encrypted data. This paper also discusses the challenges of Big Data processing protection and highlights its differences from traditional data protection. Existing works on homomorphic encryption are technically reviewed and compared in terms of their encryption scheme, homomorphism classification, algorithm design, noise management, and security assumption. Finally, this paper discusses the current implementation, challenges, and future direction towards a practical homomorphic encryption scheme for securing outsourced Big Data computation.

• The Journal of Information Systems
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• v.29 no.1
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• pp.23-50
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• 2020

Purpose As information management grows in importance around the world, organizations are investing in information security technology. However, the higher the level of information security technology in an organization, the higher the techno-stress of employees. The purpose of this study is to suggest stress factors related to information security technology that affect the reduction of employees' intention to comply with information security and to suggest ways to alleviate stress. Design/methodology/approach The research presented a model for mitigating technical stress related to information security based on technical stress theory and person-organization fit theory. 346 questionnaire data were analyzed from the members of the organization who applied the information security technology, and the research hypothesis was verified through the structural equation modeling. Findings The hypothesis test confirms that security-related techno-stress reduces the information security compliance intention of employees, organizational technical support mitigates technical stress, and person-organization fitness mitigates the negative relationship between techno-stress and compliance intention. The results of the study contribute to the organization's strategy for minimizing the reduction of the information security compliance intention of employees, and are meaningful in that the theoretical basis for mitigating techno-stress is provided in the field of information security.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.67-79
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• 2023

Service environments through laptops, smart devices, and various IoT devices are developing very rapidly. Recent security measures in these Internet environments mainly consist of network application level solutions such as firewall(Intrusion Prevention Systems) and IDS (intrusion detection system). In addition, various security data have recently been used on-site, and issues regarding the management and destruction of such security data have been raised. Products such as DRM(Digital Rights Management) and DLP(Data Loss Prevention) are being used to manage these security data. However despite these security measures, data security measures taken out to be used in the field are operated to the extent that the data is encrypted, delivered, and stored in many environments, and measures for encryption key management or data destruction are insufficient. Based on these issues we aim to propose a SecureOS Module, an OS-based security module. With this module users can manage and operate security data through a consistent interface, addressing the problems mentioned above.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2719-2735
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• 2015

In the cloud environment, users pay more attentions to their data security since all of them are stored in the cloud server. Researchers have proposed many mutual authentication schemes for the access control of the cloud server by using the smart card to protect the sensitive data. However, few of them can resist from the smart card lost problem and provide both of the forward security and the backward security. In this paper, we propose a novel authentication scheme for cloud computing which can address these problems and also provide the anonymity for the user. The trick we use is using the password, the smart card and the public key technique to protect the processes of the user's authentication and key exchange. Under the Elliptic Curve Diffie-Hellman (ECDH) assumption, it is provably secure in the random oracle model. Compared with the existing smart card based authentication schemes in the cloud computing, the proposed scheme can provide better security degree.