Abstract
Domain Name System (DNS) log has been considered as a great source of valuable information for the decision making on government policy or business strategy because querying DNS is the first step of all Internet activities. Due to the size of DNS log, Hadoop is considered as a prominent solution, but the geographical dispersal of DNS log hinders to adopt it in an ordinary way. Hadoop assumes all data source should be located on a single Hadoop File System (HDFS), but DNS log is stored on DNS servers dispersed all over the world. To resolve this issue, a new method named “Localized Analysis & Merge (LAM)” is proposed in this paper. The proposed method enables Hadoop to analyze DNS log on the dispersed DNS servers and it reduced the whole processing time dramatically. Also, the LAM method showed that DNS log can be used to extract a lot of valuable information such as a malware detection, the access frequency over countries, etc.
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Jung, E. (2017). A Data-Driven Decision Making with Big Data Analysis on DNS Log. In: Kim, K., Joukov, N. (eds) Information Science and Applications 2017. ICISA 2017. Lecture Notes in Electrical Engineering, vol 424. Springer, Singapore. https://doi.org/10.1007/978-981-10-4154-9_49
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DOI: https://doi.org/10.1007/978-981-10-4154-9_49
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