Malicious SSL certificate detection: A step towards advanced persistent threat defence

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

25 Scopus citations

Abstract

Advanced Persistent Threat (APT) is one of the most serious types of cyber attacks, which is a new and more complex version of multistep attack. Within the APT life cycle, continuous communication between infected hosts and Command and Control (C&C) servers is maintained to instruct and guide the compromised machines. these communications are usually protected by Secure Sockets Layer (SSL) encryption, making it difficult to identify if the traffic directed to sites is malicious. This paper presents a Malicious SSL certificate Detection (MSSLD) module, which aims at detecting the APT C&C communications based on a blacklist of malicious SSL certificates. This blacklist consists of two forms of SSL certificates, the SHA1 fingerprints and the serial & subject, that are associated with malware and malicious activities. In this detection module, the network traffic is processed and all secure connections are filtered. The SSL certificate of each secure connection is then matched with the SSL certificate blacklist. This module was experimentally evaluated and the results show successful detection of malicious SSL certificates.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Future Networks and Distributed Systems, ICFNDS 2017
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450348447
DOIs
StatePublished - 19 Jul 2017
Externally publishedYes

Publication series

NameACM International Conference Proceeding Series
VolumePart F130522

Bibliographical note

Publisher Copyright:
© 2017 Association for Computing Machinery.

Keywords

  • Advanced persistent threat
  • Cyber attacks
  • Intrusion detection system
  • Malicious SSL certificate
  • Malware

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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