Towards Evasive Attacks: Anomaly Detection Resistance Analysis on the Internet
Date
2013-08
Authors
Jin, Jing
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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.
Description
Keywords
Computer science, Covert Channel Detection, Evasive Attacks, Information Security, Machine learning, Similarity Measurement, Web Bots Detection