• DocumentCode
    3659753
  • Title

    An efficient classification model for detecting advanced persistent threat

  • Author

    Saranya Chandran; Hrudya P;Prabaharan Poornachandran

  • Author_Institution
    Amrita Center for Cybersecurity, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Kollam, India
  • fYear
    2015
  • Firstpage
    2001
  • Lastpage
    2009
  • Abstract
    Among most of the cyber attacks that occured, the most drastic are advanced persistent threats. APTs are differ from other attacks as they have multiple phases, often silent for long period of time and launched by adamant, well-funded opponents. These targeted attacks mainly concentrated on government agencies and organizations in industries, as are those involved in international trade and having sensitive data. APTs escape from detection by antivirus solutions, intrusion detection and intrusion prevention systems and firewalls. In this paper we proposes a classification model having 99.8% accuracy, for the detection of APT.
  • Keywords
    "Mathematical model","Feature extraction","Malware","Vegetation","Training","Organizations"
  • Publisher
    ieee
  • Conference_Titel
    Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on
  • Print_ISBN
    978-1-4799-8790-0
  • Type

    conf

  • DOI
    10.1109/ICACCI.2015.7275911
  • Filename
    7275911