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The goal of an intrusion detection system (IDS) is to monitor activities to detect breaches in security policies of a computer system or a network. This paper focuses on anomaly detection paradigm of IDS. The goal of anomaly-based IDS is to classify intrusion based on system and network activities outside of a normal region. In this paper we employ a multipledetector set artificial immune system,...
Bagging ensemble techniques have been utilized effectively by practitioners in the field of bioinformatics to alleviate the problem of class imbalance and to improve the performance of classification models. However, many previous works have used bagging only with a single arbitrary number of iterations. In this study, we raise the question of what is the impact of altering the number of iterations/ensembles...
We explore how computational ontologies can be impactful vis-à-vis the developing discipline of "data science." We posit an approach wherein management theories are represented as formal axioms, and then applied to draw inferences about data that reside in corporate databases. That is, management theories would be implemented as rules within a data analytics engine. We demonstrate a case...
In this paper we report how we improve our Chinese grammar error detection system. We focus on the recognition of word selection error, which is the hardest error type defined in 2015 NLP-TEA shared task CGED. Four major error types was defined in CGED shared task, including redundant word error, missing word error, word selection error and word disorder error. Based on the conditional random fields...
Numerous security incidents caused by malwaresand hackers have recently utilized anti-forensic techniquesto bypass analysis and detection. It is critical to build aknowledge base that would help understand such anti-forensictechniques. In this paper, we present a forensic analysis methodto detect an anti-forensic technique which leverages timestampmanipulation in NTFS file system. Our approach analyzeshow...
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