A novel search engine to uncover potential victims for APT investigations

Shun Te Liu, Yi Ming Chen, Shiou Jing Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

Advanced Persistent Threats (APT) are sophisticated and target-oriented cyber attacks which often leverage customized malware and bot control techniques to control the victims for remotely accessing valuable information. As the APT malware samples are specific and few, the signature-based or learning-based approaches are weak to detect them. In this paper, we take a more flexible strategy: developing a search engine for APT investigators to quickly uncover the potential victims based on the attributes of a known APT victim. We test our approach in a real APT case happened in a large enterprise network consisting of several thousands of computers which run a commercial antivirus system. In our best effort to prove, the search engine can uncover the other unknown 33 victims which are infected by the APT malware. Finally, the search engine is implemented on Hadoop platform. In the case of 440GB data, it can return the queries in 2 seconds.

Original languageEnglish
Title of host publicationNetwork and Parallel Computing - 10th IFIP International Conference, NPC 2013, Proceedings
Pages405-416
Number of pages12
DOIs
StatePublished - 2013
Event10th IFIP International Conference on Network and Parallel Computing, NPC 2013 - Guiyang, China
Duration: 19 Sep 201321 Sep 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8147 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th IFIP International Conference on Network and Parallel Computing, NPC 2013
Country/TerritoryChina
CityGuiyang
Period19/09/1321/09/13

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