• DocumentCode
    1667105
  • Title

    Ctracer: Uncover C&C in Advanced Persistent Threats Based on Scalable Framework for Enterprise Log Data

  • Author

    Kai-Fong Hong ; Chien-Chih Chen ; Yu-Ting Chiu ; Kuo-Sen Chou

  • Author_Institution
    Inf. & Commun. Security Lab., Chunghwa Telecom Labs., Chung-Li, Taiwan
  • fYear
    2015
  • Firstpage
    551
  • Lastpage
    558
  • Abstract
    Advanced Persistent Threat (APT), unlike traditional hacking attempts, carries out specific attacks on a specific target to illegally collect information and data from it. These targeted attacks use special-crafted malware and infrequent activity to avoid detection, so that hackers can retain control over target systems unnoticed for long periods of time. In order to detect these stealthy activities, a large-volume of traffic data generated in a period of time has to be analyzed. We proposed a scalable solution, Ctracer to detect stealthy command and control channel in a large-volume of traffic data. APT uses multiple command and control (C&C) channel and change them frequently to avoid detection, but there are common signatures in those C&C sessions. By identifying common network signature, Ctracer is able to group the C&C sessions. Therefore, we can detect an APT and all the C&C session used in an APT attack. The Ctracer is evaluated in a large enterprise for four months, twenty C&C servers, three APT attacks are reported. After investigated by the enterprise´s Security Operations Center (SOC), the forensic report shows that there is specific enterprise targeted APT cases and not ever discovered for over 120 days.
  • Keywords
    business data processing; computer crime; digital forensics; digital signatures; invasive software; APT attack; C&C channel; C&C sessions; Ctracer; SOC; Security Operations Center; advanced persistent threat; enterprise log data; forensic report; hackers; malware; network signature; scalable framework; stealthy activities detection; stealthy command and control channel detection; targeted attacks; traffic data; Command and control systems; Computers; Electronic mail; Internet; Itemsets; Malware; Servers; Advanced Persistent Threat (APT); Command and Control (C&C); mapreduce; networking logs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (BigData Congress), 2015 IEEE International Congress on
  • Conference_Location
    New York, NY
  • Print_ISBN
    978-1-4673-7277-0
  • Type

    conf

  • DOI
    10.1109/BigDataCongress.2015.86
  • Filename
    7207270