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dc.contributor.authorKumar, Neeraj-
dc.date.accessioned2026-05-08T12:20:37Z-
dc.date.available2026-05-08T12:20:37Z-
dc.date.issued2021-05-
dc.identifier.urihttp://localhost:8081/jspui/handle/123456789/20789-
dc.guideMisra, Manojen_US
dc.description.abstractIn the modern era of information technology, users are increasingly interacting with each other using various kinds of mobile devices like laptops, tablets, smart phones etc. With this growth in mobile environment various kinds of security threats have also emerged with them. One such security threat being Phishing which is basically a type of identity theft attack in which users are tricked into revealing their personal details such as credit card numbers, password, account login details etc. Phishing attack are usually carried out through fraud emails or through counterfeit websites or through the SMS. There are many types of anti-phishing solutions that had been proposed to tackle this widely growing problem but no solution is completely able to evade this problem. Here we have proposed an efficient approach for the detection of SMS based phishing also called as Smishing. Inorder to differentiate between smishing and legitimate messages, a total of 60 different features are used. The results of our experiments show that our approach performs good with an accuracy of 98.347%.en_US
dc.language.isoenen_US
dc.publisherIIT Roorkeeen_US
dc.titleSMS-Phishing Detector: A Novel Machine Learning Based Model to Detect SMS Phishing Attacksen_US
dc.typeDissertationsen_US
Appears in Collections:MASTERS' THESES (CSE)

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