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Towards Evasive Attacks: Anomaly Detection Resistance Analysis on the Internet

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dc.contributor.advisor Offutt, Jeff Jin, Jing
dc.creator Jin, Jing 2014-08-28T03:17:39Z 2014-08-28T03:17:39Z 2013-08 en_US
dc.description.abstract The Internet is rapidly improving as a platform for deploying sophisticated interactive applications especially in Web 2.0. Although the shift from desktop-centric applications brings many benefits to web-based computing and cloud computing, such as efficient com- munication with ubiquitous access and availability, the way that Internet users share and exchange information also opens their own information to security problems. Today, attack- ers conduct malicious activities to routinely track the identities of internet-connected users, steal privacy data, abuse users personal information, and expose the users unwanted data or programs. Although these attackers can also accomplish these goals by other means, the In- ternet has made it much easier for attackers to locate victims, discover sensitive information and initiate unsolicited communication with the victims.
dc.format.extent 97 pages en_US
dc.language.iso en en_US
dc.rights Copyright 2013 Jing Jin en_US
dc.subject Computer science en_US
dc.subject Covert Channel Detection en_US
dc.subject Evasive Attacks en_US
dc.subject Information Security en_US
dc.subject Machine Learning en_US
dc.subject Similarity Measurement en_US
dc.subject Web Bots Detection en_US
dc.title Towards Evasive Attacks: Anomaly Detection Resistance Analysis on the Internet en_US
dc.type Dissertation en Doctoral en Computer Science en George Mason University en

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