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Outlier detection has been shown to be a promising machine learning technique for a diverse array of felds and problem areas. However, traditional, supervised outlier detection is not well suited for problems such as network intrusion detection, where proper labelled data is scarce. This has created a focus on extending these approaches to be unsupervised, removing the need for explicit labels, but...
The Center for Strategic and International Studies estimates the annual cost from cyber crime to be more than $400 billion. Most notable is the recent digital identity thefts that compromised millions of accounts. These attacks emphasize the security problems of using clonable static information. One possible solution is the use of a physical device known as a Physically Unclonable Function (PUF)...
In nuclear facilities, having efficient accountability of critical assets, personnel locations, and activities is essential for productive, safe, and secure operations. Such accountability tracked through standard manual procedures is highly inefficient and prone to human error. The ability to actively and autonomously monitor both personnel and critical assets can significantly enhance security and...
The Hadoop MapReduce software environment is used for parallel processing of distributively stored data. Data mining algorithms of increasing sophistication are being implemented in MapReduce, bringing new challenges for performance measurement and tuning. We focus on analyzing a job after completion, utilizing information collected from Hadoop logs and machine metrics. Our analysis, inspired by [1]...
Network measurement is a discipline that provides the techniques to collect data that are fundamental to many branches of computer science. While many capturing tools and comparisons have made available in the literature and elsewhere, the impact of these packet capturing tools on existing processes have not been thoroughly studied. While not a concern for collection methods in which dedicated servers...
As scientific computing users migrate to petaflop platforms that promise to generate multi-terabyte datasets, there is a growing need in the community to be able to embed sophisticated data analysis algorithms in the storage systems for the computing platforms. Data Warehouse Appliances (DWAs) are an attractive option for this work, due to their ability to process massive datasets efficiently. While...
The challenges and solutions required for peer-to-peer video-on-demand (P2P VoD) provided by a fixed provider such as a cable company are fundamentally different from those seen in traditional P2P networks or client-server VoD solutions. Unlike traditional P2P networks, the end nodes (set top boxes with DVR capabilities) are largely under control of the system provider. Consequently, issues like churn...
This paper presents and experimentally analyzes the performance of three parallelization strategies for the popular open-source Snort network intrusion detection system (NIDS). The parallelizations include 2 conservative variants and 1 optimistic scheme. The conservative strategy parallelizes inspection at the level of TCP/IP flows, as any potential inter-packet dependences are confined to a single...
This paper investigates randomization and replication as strategies to achieve reliable performance in disk arrays targeted for video-on-demand (VoD) workloads. A disk array can provide high aggregate throughput, but only if the server can effectively balance the load on the disks. Such load balance is complicated by two key factors: workload hotspots caused by differences in popularity among media...
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