1 / 25

SURVEY ON BOTNET: ITS ARCHITECTURE, DETECTION, PREVENTION AND MITIGATION

SURVEY ON BOTNET: ITS ARCHITECTURE, DETECTION, PREVENTION AND MITIGATION . Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on. 102064535 黃川洁. Outline. INTRODUCTION BOTNET LIFE CYCLE BOTNET ARCHITECTURES DETECTION OF BOTNET ATTACK

armine
Télécharger la présentation

SURVEY ON BOTNET: ITS ARCHITECTURE, DETECTION, PREVENTION AND MITIGATION

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. SURVEY ON BOTNET: ITS ARCHITECTURE, DETECTION, PREVENTION AND MITIGATION Networking, Sensing and Control (ICNSC), 2013 10th IEEE International Conference on 102064535 黃川洁

  2. Outline • INTRODUCTION • BOTNET LIFE CYCLE • BOTNET ARCHITECTURES • DETECTION OF BOTNET ATTACK • PREVENTION & MITIGATION OF BOTNET • FUTURE PROSPECTS • CONCLUSION

  3. INTRODUCTION-1 • BOTNET is a large network of compromised computers used to attack other computer systems for malicious intent. • NetBusand BackOrifice2000 • several techniques for BOTNET attack detection • data mining, fuzzy logic based on some statistical data, anomaly based, structure based

  4. INTRODUCTION-2 • Testbedenvironment should focus on following requirements: • The ability to test with a variability of bot types (both known and unknown) deploy on variety of standard operating system. • To be capable of conducting experiments in a secure mode such as one that poses no threat to the greater internet • To be able to form a flexible and realistic botnet technologies and configuration. • To perform and conduct experiments at scale and under realistic conditions.

  5. BOTNET LIFE CYCLE-1 • In start it primarily infects other computer. • Then injects small code • File Transfer Protocol (FTP), Hypertext Transfer Protocol (HTTP), Peer to Peer (P2P), and combination of HTTP and P2P (HTTP2P) etc. • When user connects to internet code is executed automatically to establish a connection in which it connects to Command & Control (C&C) server.

  6. BOTNET LIFE CYCLE-2 • Command and control the zombie computers through C & C server. • To remain transparent and active by using Dynamic Domain Name Server (DNS) and keeping zombie updated and in existence to maintain and use them accordingly.

  7. BOTNET ARCHITECTURES • Centralized Botnet Architecture • Peer to Peer (P2P) Botnet Architecture • Hybrid Botnet Architecture • Hypertext Transfer Protocol Peer to Peer (HTTP2P) Botnet Architecture

  8. Centralized Botnet Architecture

  9. Peer to Peer (P2P) Botnet Architecture

  10. Hybrid Botnet Architecture

  11. Hypertext Transfer Protocol Peer to Peer (HTTP2P) Botnet Architecture • P2P has threat of Sybil attacks • Sybil Attack:是一種攻擊者透過大量匿名實體增加不成比例的巨大影響,來破壞P2P網路的信譽系統。(TWCERT/CC) • Combined HTTP and P2P • Become harder to be detected by to bypass firewall and client server architecture • Cipher the message • While the Soldier-Bot does not contact dynamically to Supervisor-Bot or other soldier-bots rather it waits for a call from its supervisor.

  12. DETECTION OF BOTNET ATTACK • Structured Based Detection • Signature Based Detection • DNS Based Detection • Behavior Based Detection • Anomaly Based Detection • Communication Pattern of Botnet

  13. Signature Based Detection • The first and most widely • Only successful for already known Botnets • Two way • list of IRC nicknames and applied n-gram analysis • IP addresses • Other system • Honeynet, Honeypots, and Snort • good cost and without false positives

  14. DNS Based Detection-1 • DNS queries • In 2004-05 ideas were given to detect domain names by unusually high or temporary intense DDNS queries. • In following year, abnormally recurring NXDOMAIN reply rates approach was proposed.

  15. DNS Based Detection-2 • Passive analysis of DNS based Black-hole list (DNSBL) lookup traffic • Two problems • high false positive • cannot detect distributed inspection • Hyunsang Choi et al

  16. Anomaly Based Detection-1 • high network latency, high volumes of traffic, traffic on unusual ports, and unusual system behavior • cannot detect a BOTNET in sleeping mode • Binkley and Singh solved by combining TCP based anomaly with IRC tokenization and IRC message statistics to create a system

  17. Anomaly Based Detection-2 • Gu et al. have proposed Botsniffer • Botnet C&C channels • local area network • low false positive • Basheer Al-Duwairi and Lina Al-Ebbini proposed BotDigger • fuzzy logic • not work on a specific pattern • the most reliable and flexible

  18. Communication Pattern of Botnet -1 • Cyber security defenders checks the communication characteristics between a Supervisor-Bot and a Soldier-Bot on transport layer such as for TCP or UDP. • Defenders check its source and destination IP, Port and Protocol Identifier. • Static characteristics • header • dynamic characteristics • arrival, departure, throughput, and burst time of payload information

  19. Communication Pattern of Botnet-2 • selecting precise set of characteristic and defining unique flow as object • comparing with other objects provide more information • encrypted with the evolution of Botnet • data mining techniques are applied on that limited data to overcome the problem

  20. PREVENTION & MITIGATION OF BOTNET • In 2007 Collins et al. work to detect future botnet address by the help of unclean network • spatial (compromised hosts to cluster) • temporal (tendency to contain compromised hosts for extended period) • Alex Brodsky et al. proposed a distributed content independent spam classification system to defend from Botnet generated Spam’s. • Trend Micro provided Botnet Identification services • real- time Botnet C&C bot-master address list

  21. FUTURE PROSPECTS-1 • Some of the steps to be taken to study the mind of supervisor- bot are as follow: • Make data warehouse of known bots for future use in data mining, and to make an algorithm to use that data as mitigation for attacks. • Honeypots based defense is so popular and used mostly; it is predicted and possible that one day supervisor- bots will have a defense mechanism for detection of honeypots in their bots.

  22. FUTURE PROSPECTS-2 • To make anti-bot application software which can work against Botnet attack as antivirus does against viruses etc. • New Testbeds are required to be developed which allow testing in large-scale network either open or closed environments. • Getting of Botnet sample code is required for analyzing but criminals don’t want to examine their malware as well as cyber defender also feels hesitation with un-trusted ones.

  23. CONCLUSION • In this survey we analyzed the protocols being used by the Supervisor-bots and how they evolved with the passage of time. How cyber defenders proposed and work for the detection of a cyber-attack from known and unknown BOTNETs and given ideas and techniques for its prevention and mitigation. But unfortunately for prevention and mitigation till now no sufficient work has been done.

  24. Thank You

More Related