2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) 2014
DOI: 10.1109/wi-iat.2014.127
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Support Vector Machine for Malware Analysis and Classification

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Cited by 39 publications
(17 citation statements)
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“…Supervised learning is the task of gaining knowledge by providing statistical models with correct instance examples, during a preliminary phase called training. The supervised algorithms used by reviewed papers are rule-based classifier [11,29,30,67,40,78,60,13], Bayes classifier [61,20,26,51,35], Naïve Bayes [11,12,15,26,51,67,35], Bayesian Network [21,61,20], Support Vector Machine (SVM) [12,13,15,16,65,66,48,49,61,20,24,26,31,29,51,52,53,67,35], Multiple Kernel Learning [18], Prototype-based Classification [57], Decision Tree [12,13,15,4...…”
Section: Supervised Learningmentioning
confidence: 99%
“…Supervised learning is the task of gaining knowledge by providing statistical models with correct instance examples, during a preliminary phase called training. The supervised algorithms used by reviewed papers are rule-based classifier [11,29,30,67,40,78,60,13], Bayes classifier [61,20,26,51,35], Naïve Bayes [11,12,15,26,51,67,35], Bayesian Network [21,61,20], Support Vector Machine (SVM) [12,13,15,16,65,66,48,49,61,20,24,26,31,29,51,52,53,67,35], Multiple Kernel Learning [18], Prototype-based Classification [57], Decision Tree [12,13,15,4...…”
Section: Supervised Learningmentioning
confidence: 99%
“…Using machine learning for the identification of malware has been proposed using several different techniques by many researchers [13,14,15,16,17]. Each of these studies have their own methodologies to approach the problem of malware identification, by increasing the true positive, and reducing the false positive rate.…”
Section: Related Workmentioning
confidence: 99%
“…The algorithm presented by [22], has performed in an optimal fashion in many conventional scenarios, along with some studies similar to ours [13,14,17]. SVM creates a linear classifier, therefore, vector of weight w is its concept description and a threshold or an intercept, b.…”
Section: Svm (Support Vector Machine)mentioning
confidence: 99%
“…In recent years the important direction of research in network security is devoted to design and development of methods and tools for malicious software analysis and detection [2], [5], [7], [8], [10]. The widely used approach to malware analysis is based on the extraction of information about suspicious communication with the system, the detection of IDS signatures and the generation of new IDS signatures.…”
Section: Related Workmentioning
confidence: 99%
“…The next step is the more detailed data analysis. The widely used methods such as SVM (support vector machine) [9], [10] can be used to classify the malware data to a given campaign. The correlation graph can be applied to generate the high quality training dataset for SVM classifier.…”
Section: Campaigns Identificationmentioning
confidence: 99%