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A Comparative Study of Malware Detection System from Hadoop Perspective


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1 Pune Institute of Computer Technology, Pune, Maharashtra, India
     

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The increasing volume of data to be analyzed imposes new challenges in detecting the malware. Since data in computer servers is increasing rapidly, the analysis of these large amounts of data and to find anomaly fragments has to be done within a relevant amount of time. Malware collection and analysis are critical to the modern security industry. However, in order to face with the increasing amount of data, new parallel methods need to be developed in order to make the algorithms scalable e.g. Hadoop and MapReduce techniques. In our survey, previous attempt of a malware detection system are summarized.


Keywords

Malware, MapReduce, Hadoop.
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  • A Comparative Study of Malware Detection System from Hadoop Perspective

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Authors

Nilesh Kisanrao Dengle
Pune Institute of Computer Technology, Pune, Maharashtra, India
Shweta C. Dharmadhikari
Pune Institute of Computer Technology, Pune, Maharashtra, India

Abstract


The increasing volume of data to be analyzed imposes new challenges in detecting the malware. Since data in computer servers is increasing rapidly, the analysis of these large amounts of data and to find anomaly fragments has to be done within a relevant amount of time. Malware collection and analysis are critical to the modern security industry. However, in order to face with the increasing amount of data, new parallel methods need to be developed in order to make the algorithms scalable e.g. Hadoop and MapReduce techniques. In our survey, previous attempt of a malware detection system are summarized.


Keywords


Malware, MapReduce, Hadoop.