Malcore: Toward a practical malware identification system enhanced with manycore technology

Taegyu Kim, Ki Woong Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many conventional control flow matching methods work well, but lead to obstructive latency for the operations as the number of malware variants has soared. Even though many researchers have proposed control flow matching methods, there is still a trade-off between accuracy and performance. To alleviate this trade-off, we present a system called MalCore, which is comprised of the following three novel mechanisms, each of which aims to provide a practical malware identification system: I-Filter for identical structured control flow string matching, table division to exclude unnecessary comparisons with some malware, and cognitive resource allocation for efficient parallelism. Our performance evaluation shows that the total performance improvement is 280.9 times. This work was undertaken on a real manycore computing platform called MN-MATE.

Original languageEnglish (US)
Title of host publication1st International Conference on Information Systems Security and Privacy, ICISSP 2015
EditorsOlivier Camp, Esma Aïmeur, Edgar Weippl, Christophe Bidan
PublisherSpringer Verlag
Pages31-48
Number of pages18
ISBN (Print)9783319276670
DOIs
StatePublished - 2015
Event1st International Conference on Information Systems Security and Privacy, ICISSP 2015 - Angers, Loire Valley, France
Duration: Feb 9 2015Feb 11 2015

Publication series

NameCommunications in Computer and Information Science
Volume576
ISSN (Print)1865-0929

Conference

Conference1st International Conference on Information Systems Security and Privacy, ICISSP 2015
Country/TerritoryFrance
CityAngers, Loire Valley
Period2/9/152/11/15

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics

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