Running head: SUMMARY OF ARTICLESummary of ArticleName of the StudentStudent IDName of the UniversityAuthor’s Note:
1SUMMARY OF ARTICLEA Novel Real-Time DDoS Attack Detection Mechanism Based on MDRA Algorithm in BigDataSummary: The DoS attack, which occurs by a wide range of distributed computers, is known asthe Distributed Denial of Service or DDoS (Yu et al 2014). The Big Data technology has openedmore ways for DDoS attacks in any system. However, this type of attack can be reduced usingthe Multivariate Dimensionality Reduction Analysis or MDRA algorithm.The Denial of Service attack or DoS attack is the most significant attack in modernworld. It is a type of cyber attack, in which the hacker or the intruder seeks in a machine anddenies the service of the system. DDoS is a part of DoS attack (Joshi, Vijayan and Joshi 2012). Itconsumes the network bandwidth, memory and CPU cycle of the attacked system. Previously,there was a combined data mining approach for the detection of DDoS attack. It had anautomatic feature selection module. The Triangle Area Based Nearest Approach is anotherapproach for detecting this type of attack.The real-time DDoS detection is done by following some of the steps like collectingnetwork traffic data sample and putting them into data acquisition system. Then the processedtraffic data is fed into Big Data system (Jia et al. 2016). The method mentioned in this article isdivided into three components, which are traffic feature dimensionality reduction, traffic featurecorrelation analysis and attack detection framework based on MDRA algorithm. The PCAmethod is utilized for extraction of less dimensional and more representative features.The experiment of the MDRA algorithm is used by evaluating the data set andpretreatment, experimental results and results comparisons in terms of time cost and resourceconsumption (Alomari et al. 2012). The data set is taken into account at first and is then treated
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