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Proceedings of the 11th European Conference on Information ...

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paper c<strong>on</strong>tributes for <str<strong>on</strong>g>the</str<strong>on</strong>g> answer <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g> previous questi<strong>on</strong>s while it attempts<br />

to approach a technical and legal crossed analysis <str<strong>on</strong>g>of</str<strong>on</strong>g> traffic m<strong>on</strong>itoring<br />

alternatives, seeking to determinate whe<str<strong>on</strong>g>the</str<strong>on</strong>g>r <str<strong>on</strong>g>the</str<strong>on</strong>g> current legal establishment<br />

allows room for such strict regulati<strong>on</strong>, as <str<strong>on</strong>g>the</str<strong>on</strong>g> audiovisual industry<br />

desires, or if intellectual property defense must be sought after by<br />

some means o<str<strong>on</strong>g>the</str<strong>on</strong>g>r than traffic m<strong>on</strong>itoring.<br />

Keywords: privacy rights; internet traffic c<strong>on</strong>trol; fair balance; intellectual<br />

property rights; C-70/10<br />

Identificati<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> Topics Targeted by Attackers<br />

Manoj Cherukuri and Srinivas Mukkamala<br />

Institute for Complex Additive Systems and Analysis (ICASA), Computati<strong>on</strong>al<br />

Analysis and Network Enterprise Solutu<strong>on</strong>s (CAaNES), New Mexico<br />

Institute <str<strong>on</strong>g>of</str<strong>on</strong>g> Mining and Technology, Socorro, USA<br />

Abstract: The attackers <str<strong>on</strong>g>of</str<strong>on</strong>g>ten relied <strong>on</strong> using automated exploit kits to infect<br />

<str<strong>on</strong>g>the</str<strong>on</strong>g> legitimate websites with high traffic and inject malicious c<strong>on</strong>tent<br />

into <str<strong>on</strong>g>the</str<strong>on</strong>g>m. The compromised legitimate websites served <str<strong>on</strong>g>the</str<strong>on</strong>g> malicious c<strong>on</strong>tent<br />

to its users who ended up getting infected. In this paper we present<br />

web crawling, inlink search, topic modeling and computati<strong>on</strong>al intelligent<br />

techniques to attribute <str<strong>on</strong>g>the</str<strong>on</strong>g> topics targeted by <str<strong>on</strong>g>the</str<strong>on</strong>g> attackers. We also identify<br />

<str<strong>on</strong>g>the</str<strong>on</strong>g> attack vector used by <str<strong>on</strong>g>the</str<strong>on</strong>g> attackers with respect to <str<strong>on</strong>g>the</str<strong>on</strong>g> topics, in<br />

targeting <str<strong>on</strong>g>the</str<strong>on</strong>g> internet users. A computati<strong>on</strong>al intelligent technique relying<br />

<strong>on</strong> Gibbs random sampling was used to extract <str<strong>on</strong>g>the</str<strong>on</strong>g> topics automatically<br />

from a set <str<strong>on</strong>g>of</str<strong>on</strong>g> webpages under study. The extracted topics are correlated<br />

with Google Trends to put forward some interesting properties that are<br />

helpful in detecting <str<strong>on</strong>g>the</str<strong>on</strong>g> malicious websites proactively. We identified <str<strong>on</strong>g>the</str<strong>on</strong>g><br />

primary topics from <str<strong>on</strong>g>the</str<strong>on</strong>g> topic models generated by Gibbs random sampling<br />

across each m<strong>on</strong>th and analyzed <str<strong>on</strong>g>the</str<strong>on</strong>g> features <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>the</str<strong>on</strong>g> targeted topics with<br />

respect to its importance <str<strong>on</strong>g>the</str<strong>on</strong>g>n. We identified <str<strong>on</strong>g>the</str<strong>on</strong>g> words that were c<strong>on</strong>sistently<br />

targeted across <str<strong>on</strong>g>the</str<strong>on</strong>g> period <str<strong>on</strong>g>of</str<strong>on</strong>g> our study and analyzed <str<strong>on</strong>g>the</str<strong>on</strong>g> topics <strong>on</strong><br />

which <str<strong>on</strong>g>the</str<strong>on</strong>g> attackers are always after.<br />

Keywords: topic modeling, malicious websites, malware targeted topics,<br />

malware topic trends, malicious websites attributi<strong>on</strong>, web security<br />

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