购买名声:探索私人博客网络的生态系统

Tom van Goethem, N. Miramirkhani, W. Joosen, Nick Nikiforakis
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引用次数: 7

摘要

对许多人来说,浏览会话的开始是在流行的搜索引擎中输入相关的关键字。用户随后登陆的网站通常是由它们在搜索结果中的位置决定的。尽管人们对流行搜索引擎所采用的专有排名算法知之甚少,但人们强烈怀疑,进入的链接对结果有重大影响。这导致了各种旨在欺骗搜索引擎以推广特定网站的黑帽SEO技术的开始。在本文中,我们首次对一种新型黑帽SEO的生态系统进行了广泛的研究,即通过私人博客网络(pbn)人工创建反向链接的交易。我们的研究是三管齐下的:首先,我们进行探索性分析,通过它我们捕获生态系统的内在信息并测量反向链接的有效性。接下来,我们开发并提出了一种机器学习驱动的方法,通过利用生态系统运行中固有的各种基于内容和基于链接的特征,以98.7%的准确率检测PBN站点。最后,在一个涉及5万多个网站的大规模实验中,我们揭露了反向链接操作的大型网络,发现了数千个参与pbn的网站。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Purchased Fame: Exploring the Ecosystem of Private Blog Networks
For many, a browsing session starts by entering relevant keywords in a popular search engine. The websites that users thereafter land on are often determined by their position in the search results. Although little is known about the proprietary ranking algorithms employed by popular search engines, it is strongly suspected that the incoming links have a significant influence on the outcome. This has lead to the inception of various black-hat SEO techniques that aim to deceive search engines to promote a specific website. In this paper, we present the first extensive study on the ecosystem of a novel type of black-hat SEO, namely the trade of artificially created backlinks through private blog networks (PBNs). Our study is three-pronged: first, we perform an exploratory analysis, through which we capture intrinsic information of the ecosystem and measure the effectiveness of backlinks. Next, we develop and present an ML-driven methodology that detects PBN sites with an accuracy of 98.7% by leveraging various content-based and linking-based features intrinsic to the operation of the ecosystem. Finally, in a large-scale experiment involving more than 50,000 websites, we expose large networks of backlink operations, finding thousands of websites engaged in PBNs.
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