High Rate Denial-of-Service Attack Detection System for Cloud Environment Using Flume and Spark
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Nowadays, cloud computing is being adopted for more organizations. However, since cloud computing has avirtualized, volatile, scalable and multi-tenancy distributed nature, it is challenging task to perform attackdetection in the cloud following conventional processes. This work proposes a solution which aims to collectweb server logs by using Flume and filter them through Spark Streaming in order to only consider suspiciousdata or data related to denial-of-service attacks and reduce the data that will be stored in Hadoop DistributedFile System for posterior analysis with the frequent pattern (FP)-Growth algorithm. With the proposed system,we can address some of the difficulties in security for cloud environment, facilitating the data collection,reducing detection time and consequently enabling an almost real-time attack detection.
Abstract
Nowadays, cloud computing is being adopted for more organizations. However, since cloud computing has avirtualized, volatile, scalable and multi-tenancy distributed nature, it is challenging task to perform attackdetection in the cloud following conventional processes. This work proposes a solution which aims to collectweb server logs by using Flume and filter them through Spark Streaming in order to only consider suspiciousdata or data related to denial-of-service attacks and reduce the data that will be stored in Hadoop DistributedFile System for posterior analysis with the frequent pattern (FP)-Growth algorithm. With the proposed system,we can address some of the difficulties in security for cloud environment, facilitating the data collection,reducing detection time and consequently enabling an almost real-time attack detection.
참고문헌 (31)
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