Entity-based Parameterization for Distinguishing Distributed Denial of Service from Flash Events

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date 2018-01-03 11:44:23
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spelling 6369 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6369 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper application/pdf 2 Adobe Acrobat Pro DC 20 Paper Capture Plug-in 1.7 PDFium 2018-01-03 11:44:23 1235-01-FH03-FIK-18-12062.pdf UniSZA Private Access Entity-based Parameterization for Distinguishing Distributed Denial of Service from Flash Events In a perfect condition, there are only normal traffic and sometimes flash event traffics due to some eye-catching or heart-breaking events. Nevertheless, both events carry legitimate requests and contents to the server. Flash event traffic can be massive and damaging to the availability of the server, however, and it can easily be remedied by hardware solutions such as adding extra processing power and memory devices and software solution such as load balancing. In contrast, a collection of illegal traffic requests produced during distributed denial of service (DDoS) attack tries to cause damage to the server and thus is considered as dangerous where prevention, detection and reaction are imminent in case of occurrence. In this paper, the detection of attacks by distinguishing it from legal traffic is of our main concern. Initially, we categorize the parameters involve in the attacks in relation to their entities. Further, we examine different concepts and techniques from information theory and image processing that takes the aforementioned parameters as input and in turn decides whether an attack has occurred. In addition to that, we also pinpoint advantages for each technique, as well as any possible weakness for possible future works. International Conference on Informatics, Computing and Applied Mathematics 2017 UniSZA
spellingShingle Entity-based Parameterization for Distinguishing Distributed Denial of Service from Flash Events
summary In a perfect condition, there are only normal traffic and sometimes flash event traffics due to some eye-catching or heart-breaking events. Nevertheless, both events carry legitimate requests and contents to the server. Flash event traffic can be massive and damaging to the availability of the server, however, and it can easily be remedied by hardware solutions such as adding extra processing power and memory devices and software solution such as load balancing. In contrast, a collection of illegal traffic requests produced during distributed denial of service (DDoS) attack tries to cause damage to the server and thus is considered as dangerous where prevention, detection and reaction are imminent in case of occurrence. In this paper, the detection of attacks by distinguishing it from legal traffic is of our main concern. Initially, we categorize the parameters involve in the attacks in relation to their entities. Further, we examine different concepts and techniques from information theory and image processing that takes the aforementioned parameters as input and in turn decides whether an attack has occurred. In addition to that, we also pinpoint advantages for each technique, as well as any possible weakness for possible future works.
title Entity-based Parameterization for Distinguishing Distributed Denial of Service from Flash Events
title_full Entity-based Parameterization for Distinguishing Distributed Denial of Service from Flash Events
title_fullStr Entity-based Parameterization for Distinguishing Distributed Denial of Service from Flash Events
title_full_unstemmed Entity-based Parameterization for Distinguishing Distributed Denial of Service from Flash Events
title_short Entity-based Parameterization for Distinguishing Distributed Denial of Service from Flash Events
title_sort entity-based parameterization for distinguishing distributed denial of service from flash events