Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing

Hongda Li; Jon Oakley; Fuqiang Zhang; Hongxin Hu; Lu Yu; Richard R. Brooks

doi:10.1145/3180465.3180474

Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing

Hongda Li
, Jon Oakley
, Fuqiang Zhang
, Hongxin Hu
, Lu Yu
, Richard R. Brooks

Department of Computer Science and Engineering

Clemson University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

As data-intensive science becomes the norm in many fields of science, high-performance data transfer is rapidly becoming a core scientific infrastructure requirement. To meet such a requirement, there has been a rapid growth across university campus to deploy Science DMZs. However, it is challenging to efficiently monitor the traffic in Science DMZ because traditional intrusion detection systems (IDSes) are equipped with deep packet inspection (DPI), which is resource-consuming. We propose to develop a lightweight side-channel based anomaly detection system for traffic winnowing to reduce the volume of traffic finally monitored by the IDS. We evaluate our approach based on the experiments in a Science DMZ environment. Our evaluation demonstrates that our approach can significantly reduce the resource usage in traffic monitoring for Science DMZ.

Original language	English
Title of host publication	SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018
Publisher	Association for Computing Machinery
Pages	55-58
Number of pages	4
ISBN (Electronic)	9781450356350
DOIs	https://doi.org/10.1145/3180465.3180474
State	Published - Mar 14 2018
Event	2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, SDN-NFVSec 2018, Co-located with CODASPY 2018 - Tempe, United States Duration: Mar 21 2018 → Mar 21 2018

Publication series

Name	SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018
Volume	2018-January

Conference

Conference	2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, SDN-NFVSec 2018, Co-located with CODASPY 2018
Country/Territory	United States
City	Tempe
Period	03/21/18 → 03/21/18

Keywords

Intrusion Detection Systems
Network Function Virtualization
Science DMZ

Access to Document

10.1145/3180465.3180474

Cite this

Li, H., Oakley, J., Zhang, F., Hu, H., Yu, L., & Brooks, R. R. (2018). Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing. In SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018 (pp. 55-58). (SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018; Vol. 2018-January). Association for Computing Machinery . https://doi.org/10.1145/3180465.3180474

Li, Hongda ; Oakley, Jon ; Zhang, Fuqiang et al. / Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing. SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018. Association for Computing Machinery , 2018. pp. 55-58 (SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018).

@inproceedings{447b9d231f2d426e95e8b8ef99de507d,

title = "Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing",

abstract = "As data-intensive science becomes the norm in many fields of science, high-performance data transfer is rapidly becoming a core scientific infrastructure requirement. To meet such a requirement, there has been a rapid growth across university campus to deploy Science DMZs. However, it is challenging to efficiently monitor the traffic in Science DMZ because traditional intrusion detection systems (IDSes) are equipped with deep packet inspection (DPI), which is resource-consuming. We propose to develop a lightweight side-channel based anomaly detection system for traffic winnowing to reduce the volume of traffic finally monitored by the IDS. We evaluate our approach based on the experiments in a Science DMZ environment. Our evaluation demonstrates that our approach can significantly reduce the resource usage in traffic monitoring for Science DMZ.",

keywords = "Intrusion Detection Systems, Network Function Virtualization, Science DMZ",

author = "Hongda Li and Jon Oakley and Fuqiang Zhang and Hongxin Hu and Lu Yu and Brooks, \{Richard R.\}",

note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, SDN-NFVSec 2018, Co-located with CODASPY 2018 ; Conference date: 21-03-2018 Through 21-03-2018",

year = "2018",

month = mar,

day = "14",

doi = "10.1145/3180465.3180474",

language = "English",

series = "SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018",

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booktitle = "SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018",

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}

Li, H, Oakley, J, Zhang, F, Hu, H, Yu, L & Brooks, RR 2018, Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing. in SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018. SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018, vol. 2018-January, Association for Computing Machinery , pp. 55-58, 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, SDN-NFVSec 2018, Co-located with CODASPY 2018, Tempe, United States, 03/21/18. https://doi.org/10.1145/3180465.3180474

Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing. / Li, Hongda; Oakley, Jon; Zhang, Fuqiang et al.
SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018. Association for Computing Machinery , 2018. p. 55-58 (SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing

AU - Li, Hongda

AU - Oakley, Jon

AU - Zhang, Fuqiang

AU - Hu, Hongxin

AU - Yu, Lu

AU - Brooks, Richard R.

PY - 2018/3/14

Y1 - 2018/3/14

N2 - As data-intensive science becomes the norm in many fields of science, high-performance data transfer is rapidly becoming a core scientific infrastructure requirement. To meet such a requirement, there has been a rapid growth across university campus to deploy Science DMZs. However, it is challenging to efficiently monitor the traffic in Science DMZ because traditional intrusion detection systems (IDSes) are equipped with deep packet inspection (DPI), which is resource-consuming. We propose to develop a lightweight side-channel based anomaly detection system for traffic winnowing to reduce the volume of traffic finally monitored by the IDS. We evaluate our approach based on the experiments in a Science DMZ environment. Our evaluation demonstrates that our approach can significantly reduce the resource usage in traffic monitoring for Science DMZ.

AB - As data-intensive science becomes the norm in many fields of science, high-performance data transfer is rapidly becoming a core scientific infrastructure requirement. To meet such a requirement, there has been a rapid growth across university campus to deploy Science DMZs. However, it is challenging to efficiently monitor the traffic in Science DMZ because traditional intrusion detection systems (IDSes) are equipped with deep packet inspection (DPI), which is resource-consuming. We propose to develop a lightweight side-channel based anomaly detection system for traffic winnowing to reduce the volume of traffic finally monitored by the IDS. We evaluate our approach based on the experiments in a Science DMZ environment. Our evaluation demonstrates that our approach can significantly reduce the resource usage in traffic monitoring for Science DMZ.

KW - Intrusion Detection Systems

KW - Network Function Virtualization

KW - Science DMZ

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DO - 10.1145/3180465.3180474

M3 - Conference contribution

AN - SCOPUS:85052016764

T3 - SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018

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BT - SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018

PB - Association for Computing Machinery

T2 - 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, SDN-NFVSec 2018, Co-located with CODASPY 2018

Y2 - 21 March 2018 through 21 March 2018

ER -

Li H, Oakley J, Zhang F, Hu H, Yu L, Brooks RR. Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing. In SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018. Association for Computing Machinery . 2018. p. 55-58. (SDN-NFVSec 2018 - Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks and Network Function Virtualization, Co-located with CODASPY 2018). doi: 10.1145/3180465.3180474

Towards efficient traffic monitoring for science dmz with side-channel based traffic winnowing

Abstract

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Keywords

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