Predicting the Spread of Malware Outbreaks Using Autoencoder Based Neutral Networks

dc.contributor.authorGopika, Bhardwaj
dc.contributor.authorRashi, Yadav
dc.coverage.issue1cs
dc.coverage.volume25cs
dc.date.accessioned2020-05-05T07:21:10Z
dc.date.available2020-05-05T07:21:10Z
dc.date.issued2019-06-24cs
dc.description.abstractMalware Outbreaks are pervasive in today's digital world. However, there is a lack of awareness on part of general public on how to safeguard against such attacks and a need for increased cooperation between various national and international research as well as governmental organizations to combat the threat. On the positive side, cyber security websites, blogs and newsletters post articles outlining the working and spread of a malware outbreak and steps to recover from the same as well. In this project, an effective approach to predicting the spread of malware outbreaks is presented. The scope of the project is 15 Malware Outbreaks and the approach involves collecting these cyber aware articles from the web, assigning them to the 15 Malware Outbreaks using Topic Modeling and Similarity Analysis and along with Spread information of the Malware Outbreaks, this is input to auto encoder neural network for learning latent space representations which are further used to predict the spread of malware outbreak as either high or low spread outbreak, achieving a prediction accuracy of 75.56. This work can be used to process large amount of cyber aware content for effective and accurate prediction in the era of much-needed cyber security.en
dc.formattextcs
dc.format.extent157-164cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2018 vol. 25, č. 1, s. 157-164. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2019.1.157en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/186993
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/92cs
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0en
dc.subjectmalware outbreaksen
dc.subjecttopic modelingen
dc.subjectsimilarity analysisen
dc.subjectauto encodersen
dc.subjectpredictionen
dc.titlePredicting the Spread of Malware Outbreaks Using Autoencoder Based Neutral Networksen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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