Fatemeh Azmandian

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As virtualization technology gains in popularity, so do attempts to compromise the security and integrity of virtualized computing resources. Anti-virus software and firewall programs are typically deployed in the guest virtual machine to detect malicious software. These security measures are effective in detecting known malware, but do little to protect(More)
Virtualization technology has many attractive qualities including improved security, reliability, scalability, and resource sharing/management. As a result, virtualization has been deployed on an array of platforms, from mobile devices to high end enterprise servers. In this paper, we present a novel approach to working at a virtualization interface,(More)
Effective outlier detection requires the data to be described by a set of features that captures the behavior of normal data while emphasizing those characteristics of outliers which make them different than normal data. In this work, we present a novel non-parametric evaluation criterion for filter-based feature selection which caters to outlier detection(More)
Virtualization is becoming an increasingly popular service hosting platform. Recently, intrusion detection systems (IDSs) which utilize virtualization have been introduced. One particular challenge present in current virtualization-based IDS systems is considered in this paper. IDS systems are commonly faced with high-dimensionality imbalanced data.(More)
Acquiring a set of features that emphasize the differences between normal data points and outliers can drastically facilitate the task of identifying outliers. In our work, we present a novel non-parametric evaluation criterion for filter-based feature selection which has an eye towards the final goal of outlier detection. The proposed method seeks the(More)
Selecting features is an important step of any machine learning task, though most of the focus has been to choose features relevant for classification and regression. In this work, we present a novel non-parametric evaluation criterion for filter-based feature selection which enhances outlier detection. Our proposed method seeks the subset of features that(More)
Virtualization has gained tremendous traction as the go-to computing technology due to many advantages it offers such as server consolidation, increased reliability and availability, and enhanced security through isolation of virtual machines. Within a virtual machine itself, securing workloads against cyber attacks becomes an increasingly critical task. In(More)
Major accidents can happen during radiotherapy, with an extremely severe consequence to both patients and clinical professionals. We propose to use machine learning and data mining techniques to help detect large human errors in a radiotherapy treatment plan, as a complement to human inspection. One such technique is computer clustering. The basic idea of(More)
Cloud storage solutions have increasingly gained in popularity as they offer a convenient method of maintaining one's data all in one place, with the ability to access it from anywhere at any time. In this paper, we leverage a virtualization-based intrusion detection infrastructure to build secure cloud storage systems. The intrusion detection system uses(More)
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