Achieving High Accuracy in an Attack-Path Reconstruction in Marking on Demand Scheme

P. Banu Prakash*, E.S.Phalguna Krishna**
* PG Scholar, Department of Computer Science and Engineering, Sree Vidyanikethan Engineering College, Tirupati, India.
** Assistant Professor, Department of Computer Science and Engineering, Sree Vidyanikethan Engineering College, Tirupathi, India.
Periodicity:June - August'2016
DOI : https://doi.org/10.26634/jit.5.3.8138

Abstract

A source of a Distributed Denial-of-Service (DDoS) attacks are one of the major threats to the Internet today. DDoS attacks can be recognized by the traffic they make using the IP traceback technique [5]. In general, there are only a limited number of routers and the computers involved in an attack session are noticed. Therefore, only marking those involved nodes for traceback purpose is needed, rather than marking each node of the Internet, as the existing schemes does. Based on this finding, a novel Marking on Demand (MOD) scheme based on the DDPM mechanism to dynamicaly distribute marking IDs in both temporal and space dimensions is available. The available MOD scheme can traceback to all probable sources of DDoS attacks, which is not feasible for the existing DDPM schemes. However, the existing MOD framework needs to be extended since it suffers from both false positive and false negative rate. This paper aims to extend the existing MOD scheme by using a 32-bit marking field in order to reduce the shortcomings and to avoid the problem caused by packet fragmentation due to increase in marking length.

Keywords

DDOS Attack, DDPM, IP Traceback, Packet Marking, Path Reconstruction, MOD.

How to Cite this Article?

Prakash. P. B and Krishna. E. S. P (2016). Achieving High Accuracy in an Attack-Path Reconstruction in Marking on Demand Scheme. i-manager’s Journal on Information Technology, 5(3), 24-29. https://doi.org/10.26634/jit.5.3.8138

References

[1]. Shui Yu, Wanlei Zhou, Song Guo, and Minyi Guo, (2015). “A Feasible IP Traceback Framework through Dynamic Deterministic Packet Marking”. IEEE Transactions on Computers, pp.1-11.
[2]. Anatolii Balyk, Uliana Latsykovska, Mikolaj Karpinski, Yuliia Khokhlachova, Aigul Shaikhanova, and Lesia Korkishko, (2015). “A Survey of Modern IP Traceback Methodologies”. IEEE International Conference IDAACS, pp. 484-488.
[3]. Shui Yu, Wanlei Zhou, Song Guo, and MinyiGuo, (2009). “Flexible Deterministic Packet Marking: An IP Traceback System to Find the Real Source of Attacks”. IEEE Transactions on Parallel and Distributed Systems, Vol. 20, No. 4, pp. 567-580.
[4]. Yinan Jing, Xueping Wang, Xiaochun Xiao, and Gendu Zhang, (2006). “Defending Against Meek DDoS Attacks By IP Traceback-based Rate Limiting”. IEEE Globecom.
[5]. Ashley Chonka, Wanlei Zhou, and Jaipal Singh, (2008). “Detecting and Tracing DDoS attacks by Intelligent Decision Prototype”. IEEE International Conference on Pervasive Computing and Communications, DOI 10.1109.
[6]. Long Cheng, Dinil Mon Divakaran, Wee Yong Lim, Vrizlynn and L.L. Thing, (2016). “Opportunistic Piggyback Marking for IP Traceback”. IEEE Transactions on Information Forensics and Security, Vol. 11, No. 2, pp. 273288, DOI 10.1109/ TIFS.2015.2491299.
[7]. Ming-Hour Yang and Ming-Chien Yang, (2012). “RIHT: A Novel Hybrid IP Traceback Scheme”. IEEE Transactions on Information Forensics and Security, Vol. 7, No. 2.
[8]. ShuiYu, Wanlei Zhou, Robin Doss, and Weijia Jia, (2011). “Traceback of DDoS Attacks Using Entropy Variations”. IEEE Transactions on Parallel and Distributed Systems, Vol. 22, No. 3.
[9]. M. Parameswari and S. Sukumaran, (2016). “Dynamic Detection and Protection Mechanism against Distributed Denial of Service Attacks using Fuzzy Logic”. International Journal of Applied Engineering Research, ISSN 0973- 4562, Vol. 11, No. 7, pp 5332-5337.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.