Abstract
To protect the computer and internet users from exposing themselves towards malware attacks, identifying the attacks through investigating malware log file is an essential step to curb this threat. The log file exposes crucial information in identifying the malware, such as algorithm and functional characteristic, the network interaction between the source and the destination, and type of malware. By nature, the log file size is humongous and requires the investigation process to be executed on faster and stable platform such as big data environment. In this study, Hadoop technology used to process and extract the information from the malware log files that obtains from university's security equipment. The Python program was used for data transformation then analysis it in Hadoop simulation environment. The results of log processing have reduced 50% of the original log file size, while the total execution time would not increase linearly with the size of the data.
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More From: International Journal of Digital Enterprise Technology
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