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Identifying anomalous events in the network is one of the vital functions in enterprises, ISPs, and datacenters to protect the internal resources. With its importance, there has been a substantial body of work for network anomaly detection using supervised and unsupervised machine learning techniques with their own strengths and weaknesses. In this work, we take advantage of the both worlds of unsupervised...
Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this paper, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus...
While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this work, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring...
Biological network inference is of importance to understand underlying biological mechanisms. Gene regulatory networks describe molecular interactions of complex biological processes. Graph models are mainly used for gene regulatory networks, where nodes and edges represent genes and their regulations respectively. In the most research, the molecular interactions (edges) of gene regulatory networks...
Network traffic classification is one of the essential functions for local and ISP networks. With its importance, a substantial number of previous studies have explored various machine learning techniques with network flow statistics for accurate traffic classification, including the clustering-based approach. However, we obtained unacceptable results from previously proposed clustering-based techniques...
Cyber-attacks have been evolved in a way to be more sophisticated by employing combinations of attack methodologies with greater impacts. For instance, Advanced Persistent Threats (APTs) employ a set of stealthy hacking processes running over a long period of time, making it much hard to detect. With this trend, the importance of big-data security analytics has taken greater attention since identifying...
We propose a computational model based on OWL/SWRL enabled ontologies, which can shape the development of an automated software tool for the purpose of providing patient-specific reminders, advice and action-items in preventing the development of diabetic foot in diabetic patients. The tool is aimed at both: (i) patients who would like to manage their illness efficiently by being informed and alerted...
The Differentiated Services architecture represents a highly scalable architecture for deployment of Quality of Services across the next-generation Internet. The Differentiated Services enable the packets that pass through network devices operating on layer 3 information, such as routers, to have their relative priority differentiated from one another. With Differentiated Services marking, Layer 3...
The process of building applications using semantic web and the knowledge repositories has many challenges associated with it. One of them is that information security is still a major issue with protecting these knowledge repositories that helps in interaction, integration, and interoperability between computing devices and applications. We believe that Elliptic Curve Cryptography provides a convenient...
Clustering is a data mining technique, in which objects of similar characteristics are grouped together to form a cluster. Traditional clustering algorithms use distance metric measures to form clusters out of data which produce unstable results. More over traditional clustering algorithms (e.g., k-means) can implement the distance metric methods only on numeric data. This paper focuses on hybrid...
Ontology is a technique that represents data as a set of concepts within a domain and the relativity of those concepts [16]. It is used to give the rationale to the entities within the domain, and can also be used to describe about it [21]. Clustering organizes data into individual clusters. In this article we are proposing a model which uses the hierarchical relationships. We group related item sets...
This paper discusses about methodology to implement a search engine. Most of the common techniques employed in search engine are based on the term frequency. To achieve a more accurate analysis, the underlying representation should indicate terms that capture the concepts of text. In this paper we present how the concepts can be represented using Hierarchy of Attributes and concepts using clustering...
In this paper, a report on high PAE, high breakdown-voltage HEMTs grown by ammonia MBE is discussed. First, an AlN nucleation layer was grown by plasma-assisted MBE on SiC. Then GaN buffer was grown by ammonia MBE, followed by 30 nm ammonia Al0.3Ga0.7N. A sheet charge of 1x1013 cm-2 with a mobility of 1500 cm2V-1s-1 was obtained from Hall measurements.
In this report we present the switching measurements on large area AlGaN/GaN HEMT devices with high breakdown voltage achieved with the help of multiple field plates. AlGaN/GaN high electron mobility transistors have shown potential advantages over Si and SiC based transistors for high power switching. The very high electron mobility in the AlGaN/GaN HEMT system combined with the high density of polarization...
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