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dc.contributor.author Agrawaal, Taneea S
dc.contributor.author Kumaraguru, Ponnurangam (Advisor)
dc.date.accessioned 2018-09-25T10:17:09Z
dc.date.available 2018-09-25T10:17:09Z
dc.date.issued 2017-07-07
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/696
dc.description.abstract Darknet markets, also known as cryptomarkets, are websites located on the Darknet and designed to allow the traffcking of illicit products, mainly drugs. Over the past decade, online advertising became the principal economic force behind many an Internet service, from major search engines to globe-spanning social networks to blogs. There is often a tension between online advertising and user experience, but on the other hand, advertising revenue enables a myriad of free Web services to the public and fosters a great deal of innovation. We make use of a public dataset made available in 2016 consisting of a collection of 89 black markets and 37 darknet forums to conduct various elementary experiments done to derive basic characteristics such as anonymity, vendor-product relationships from the data. With the emergence of computational advertising - which strives to make online advertising integral to the user experience,this paper focuses on various IR and Natural Language Processing techniques employed to study and analyze computational advertising and use of manipulative techniques on the dark net. Wediscuss the feature engineering required for such a large dataset in detail. en_US
dc.language.iso en_US en_US
dc.publisher IIIT-Delhi en_US
dc.subject Darknet en_US
dc.subject Digital cryptomarket en_US
dc.subject Computational advertising en_US
dc.title Digital cryptomarkets en_US
dc.type Other en_US


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