Adaptive load balancing architecture for SNORT

被引:0
|
作者
Alam, MS [1 ]
Javed, Q [1 ]
Akbar, M [1 ]
Rehman, MRU [1 ]
Anwer, MB [1 ]
机构
[1] Natl Univ Sci & Technol, Mil Coll Signals, Rawalpindi 46000, Pakistan
关键词
intrusion detection; traffic splitting; snort; sensor cluster; misuse detection;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Nowadays the importance of intrusion detection is amplified due to incredible increase in number of attacks on the networks. The ubiquity of the Internet and the easy perpetration of the attacks will lead to more hostile traffic on the Internet. With the advent of high-speed Internet connections, the organizations today rind it difficult to detect intrusions. So multi sensor Intrusion Detection Systems are inevitable. The optimum distribution of traffic to the sensors is a challenging task. In this paper we present a mechanism to split traffic to different intrusion detection sensors to make the task manageable. This splitting of traffic to each sensor is managed by policies enforced on the splitter by the management console. The system is adaptive in the sense that it can adjust the splitting policies for keeping load disparity among sensors reduced. This mechanism of policy- reloading also take into the account the similarity between all possible pairs of policies and tries to minimize the packet duplication rate during the operation of the system. Our mechanism is based on the observation that minimizing the percentage of traffic being duplicated can enhance system performance. We have also discussed the effects of reloading of splitting policies on packet duplication rate and load on sensors.
引用
收藏
页码:48 / 52
页数:5
相关论文
共 50 条
  • [1] A New Architecture for Internet Load Balancing Using Adaptive Packet Scheduling
    Azath, M.
    Banu, R. S. D. Wahida
    [J]. 2009 2ND IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 4, 2009, : 94 - 98
  • [2] Adaptive Job Load Balancing Scheme on Mobile Cloud Computing with Collaborative Architecture
    Kim, Byoungwook
    Byun, Hwirim
    Heo, Yoon-A
    Jeong, Young-Sik
    [J]. SYMMETRY-BASEL, 2017, 9 (05):
  • [3] Adaptive Load Balancing in KAD
    Carra, Damiano
    Steiner, Moritz
    Michiardi, Pietro
    [J]. 2011 IEEE INTERNATIONAL CONFERENCE ON PEER-TO-PEER COMPUTING (P2P), 2011, : 92 - 101
  • [4] Adaptive load balancing and multithreading
    Melab, N
    Lecouffe, MP
    Devesa, N
    Toursel, B
    [J]. PARALLEL AND DISTRIBUTED COMPUTING SYSTEMS - PROCEEDINGS OF THE ISCA 9TH INTERNATIONAL CONFERENCE, VOLS I AND II, 1996, : 343 - 348
  • [5] Enhanced GridSim architecture with load balancing
    Kalim Qureshi
    Attiqa Rehman
    Paul Manuel
    [J]. The Journal of Supercomputing, 2011, 57 : 265 - 275
  • [6] A Dynamic Load Balancing Architecture for SDN
    Sufiev, Hadar
    Haddad, Yoram
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON THE SCIENCE OF ELECTRICAL ENGINEERING (ICSEE), 2016,
  • [7] Simulation of Load Balancing in Parallel Architecture
    Thakur, Varsha
    Kumar, Sanjay
    [J]. 2017 7TH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT), 2017, : 113 - 118
  • [8] Enhanced GridSim architecture with load balancing
    Qureshi, Kalim
    Rehman, Attiqa
    Manuel, Paul
    [J]. JOURNAL OF SUPERCOMPUTING, 2011, 57 (03): : 265 - 275
  • [9] Application of Adaptive Load Balancing Algorithm Based on Minimum Traffic in Cloud Computing Architecture
    Kang, Lu
    Ting, Xing
    [J]. 2015 INTERNATIONAL CONFERENCE ON LOGISTICS, INFORMATICS AND SERVICE SCIENCES (LISS), 2015,
  • [10] On fully distributed adaptive load balancing
    Breitgand, David
    Cohen, Rami
    Nahir, Amir
    Raz, Danny
    [J]. MANAGING VIRTUALIZATION OF NETWORKS AND SERVICES, PROCEEDINGS, 2007, 4785 : 74 - +