Abstract
In this paper, for the detection of the masquerade attacks in the cloud infrastructure collaborative filtering algorithm based on the cloud model is proposed. One of the advantages of this model is the identification of the similarity between the users on the basis of the cloud model. While using the similarity measurement method based on the cloud model, it does not require a strict comparison between the score value of operations used by different users. Here we provide the calculation of the statistic features of the score values of all operations used by the user at the access point, then we provide a comparison of statistics features of the input data and based of these we determine the similarity between the input data.
Highlights
The emergence of the cloud computing technologies nowadays has significantly changed the way we use the computer means as well as the way we access and store our personal and business information
Among these threats the 1st and the 3d threats can be implemented in each layer of the cloud computing SPI (Service Platform Infrastructure) model
According to the cybercrime watch survey [3] conducted by the organization CERT in 2010, the first place among the top 5 electronic crimes belongs to viruses, worms and other malicious codes, the second part takes the unauthorized access
Summary
Among these threats the 1st and the 3d threats can be implemented in each layer of the cloud computing SPI (Service Platform Infrastructure) model. A masquerader, who gets access to the victim’s system illegitimately is unlikely to be familiar with the structure and the contents of the file system His search is likely to be widespread and untargeted as well as the type and sequence of commands applied by the users in the system are being different. Taking this into account, the user’s profile reflecting his search behavior is created at [13, 15] and the one-class modeling technique is developed in order to detect the illegal intrusion. The Feature Extraction Tool generates the feature vector based on cloud model for the user
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