• DocumentCode
    625216
  • Title

    Detecting and Analyzing Zero-Day Attacks Using Honeypots

  • Author

    Musca, Constantin ; Mirica, Emma ; Deaconescu, Razvan

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. Politeh. of Bucharest, Bucharest, Romania
  • fYear
    2013
  • fDate
    29-31 May 2013
  • Firstpage
    543
  • Lastpage
    548
  • Abstract
    Computer networks are overwhelmed by self propagating malware (worms, viruses, trojans). Although the number of security vulnerabilities grows every day, not the same thing can be said about the number of defense methods. But the most delicate problem in the information security domain remains detecting unknown attacks known as zero-day attacks. This paper presents methods for isolating the malicious traffic by using a honeypot system and analyzing it in order to automatically generate attack signatures for the Snort intrusion detection/prevention system. The honeypot is deployed as a virtual machine and its job is to log as much information as it can about the attacks. Then, using a protected machine, the logs are collected remotely, through a safe connection, for analysis. The challenge is to mitigate the risk we are exposed to and at the same time search for unknown attacks.
  • Keywords
    computer network security; invasive software; virtual machines; Snort intrusion detection system; Snort intrusion prevention system; computer network; honeypot system; information security domain; malware; security vulnerability; virtual machine; zero-day attack analysis; zero-day attack detection; Dictionaries; IP networks; Operating systems; Ports (Computers); Protocols; Security; Virtual machining; honeypot; intrusion detec- tion/prevention system; zero-day attacks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Systems and Computer Science (CSCS), 2013 19th International Conference on
  • Conference_Location
    Bucharest
  • Print_ISBN
    978-1-4673-6140-8
  • Type

    conf

  • DOI
    10.1109/CSCS.2013.94
  • Filename
    6569317