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Extended Abstract: Detecting Scareware by Mining Variable Length Instruction Sequences
Responsible organisation
2011 (English)Conference paper, Published paper (Refereed) Published
Abstract [en]

This paper presents a scareware detection method that is based on performing data mining on extracted variable length opcode sequences derived from instruction sequences of binary files. Our experimental results show that many common supervised learning algorithms generate accurate models from subsets of our data set.

Place, publisher, year, edition, pages
Trondheim: IOS Press , 2011.
Keyword [en]
Scareware, Instruction Sequences, Classification
National Category
Computer Science
Identifiers
URN: urn:nbn:se:bth-7558Local ID: oai:bth.se:forskinfo56A7FA91129D76B7C125789A002C8A83ISBN: 978-1-60750-753-6 (print)OAI: oai:DiVA.org:bth-7558DiVA: diva2:835183
Conference
11th Scandinavian Conference on Artificial Intelligence
Available from: 2012-09-18 Created: 2011-05-24 Last updated: 2015-06-30Bibliographically approved

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fulltext(130 kB)41 downloads
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File name FULLTEXT01.pdfFile size 130 kBChecksum SHA-512
be5a7f0bc08caf8d359c18cd9032ed217c7f55fc7c9ce2fa839071212d74ccebadc1ee21cb8eddc8eac2ee9d0a99dfcb1de115a2dba2c489cd3126421b49ba04
Type fulltextMimetype application/pdf

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Lavesson, Niklas
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CiteExportLink to record
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