Analytic Hierarchy Process (AHP) to Find Most Probable Web Attack on an E-Commerce Site

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dc.contributor.author Lokhande, P. S.
dc.date.accessioned 2016-09-14T10:58:18Z
dc.date.available 2016-09-14T10:58:18Z
dc.date.issued 2016-03-04
dc.identifier.citation Lokhande, P (2016). Analytic Hierarchy Process (AHP) to Find Most Probable Web Attack on an E-Commerce Site. International Conference on Information and Communication Technology for Competitive Strategies (ICTCS-2016), 62. en_US
dc.identifier.isbn 978-1-4503-3962-9
dc.identifier.uri http://www.aiktcdspace.org:8080/jspui/handle/123456789/1789
dc.description Second International Conference on Information and Communication Technology for Competitive Strategies (ICTCS-2016) - Udaipur, Rajasthan, India. en_US
dc.description.abstract Attackers are using various techniques to attack on an E-Commerce site; they do have various options to initiate attack. On other hand web administrators finding it difficult to prioritize the defense mechanism against each web attack. The Analytic Hierarchy Process (AHP) is an effective method in dealing with the situations where we need to select one among available alternatives or prioritize them according to their severity. Here we try to focus on some major type of attacks which are most offensively happening on the web-services; like Cross-Site Scripting Attack, DoS Attack, SQL Injection Attack and Man-in-Middle Attack. These top online web attack methods were chosen to decide the most probable happening attack on a website. The prposed methods shows step by step approach to find the most probable alternative that hackers could first use to do the attack.On the basis of this model the administrator can take care of it at first place. en_US
dc.language.iso en_US en_US
dc.publisher ACM: Association For Computing Machinery en_US
dc.relation.ispartofseries ICTS-2016;Article No. 62
dc.subject Staff Publication - SoET en_US
dc.subject Staff Publication - CO en_US
dc.title Analytic Hierarchy Process (AHP) to Find Most Probable Web Attack on an E-Commerce Site en_US
dc.type Article en_US


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