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The Research and Implementation of Detection System on Cloaked Web Pages

Author: Deng
Tutor: ChenHao
School: Hunan University
Course: Computer Science and Technology
Keywords: Cloak SEO Crawler Similarity Multi-features Search Engine
CLC: TP391.3
Type: Master's thesis
Year: 2013
Downloads: 8
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Abstract


With the continuous development of the Internet technology and rapid increase ofnetwork information, the dependency on the computer network and the requirementsof the network information search for human society become increasingly high.Search engines become an indispensable channel of connecting personal and networkresources. Black hat SEO techniques are often used to improve rankings in searchengines’ result, and also to increase network traffic. Cloaking is one of the mostlyused black hat SEO techniques that present a different page to users depending onwhether the page is being requested by a human visitor or a search engine.Existing cloaking detection methods are limited in accuracy. This paper presentsan optimizing similarity detection algorithm based on three features in web pages.The algorithm extracts the features of text, tag, URL in web pages, and respectivelycompares the similarity of each feature. Aiming at improving the accur acy, thismethod uses hierarchical filtering steps to exclude pages with high similarity bysetting threshold values. We firstly crawl the HTML content of each URL for5timesthrough mimicking different roles. Each pair of documents are compared to recogn izethe cloaking type. Existing systems are unable to detect JavaScript RedirectionCloaking. We tackle this problem by driving a JavaScript engine to detect redirectionof each web pages. Results show we could detect JavaScript Redirection Cloakingsuccessfully.We implement a prototype detection system which adopts the above methods. Thesystem crawls each URL for5times through changing the HTTP request header,invoking built-in JavaScript engine, crawling cached contents. We detect thesimilarity of each document pair using our algorithm to identify the cloaked pages.We apply our system on Yahoo’s search engine, and crawl the100,000URLs fromsearch results. We choose5000URLs as our sample data set, and manually mark1000URLs among them. This paper takes several steps to reduce the time consumption,including duplicate removal, white list filtering and multi-threads. Tests on a largenumber of sample data set show that our system could gain good result in the accuracy of detection, identifying cloaked pages and time consumption. Particularly, themethods used in this paper can detect more types of cloaking techniques includingUser Agent Cloaking, IP Cloaking, Referrer Cloaking, and JavaScript Cloaking.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Retrieval machine
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