Abstract
Big data processing frameworks such as Hadoop [1] are now widely adopted, however the security issues in large scale systems have not been well studied yet. Unlike prior work on data privacy and protection, this paper investigates a potential attack from a compromised internal node against the overall system performance. We develop an effective attack launched from the compromised node that can significantly degrade the data processing performance of the cluster without being detected and blacklisted for job execution, also present a mitigation scheme that protects a Hadoop system from such attack. The results of experiments show that this attack greatly slows down the job executions in the native Hadoop system even with some basic defense mechanisms, however, our mitigation schem can keep the whole cluster running efficiently under such attack.
| Original language | English |
|---|---|
| Title of host publication | 2017 International Conference on Computing, Networking and Communications, ICNC 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 525-530 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509045884 |
| DOIs | |
| State | Published - 10 Mar 2017 |
| Event | 2017 International Conference on Computing, Networking and Communications, ICNC 2017 - Silicon Valley, United States Duration: 26 Jan 2017 → 29 Jan 2017 |
Publication series
| Name | 2017 International Conference on Computing, Networking and Communications, ICNC 2017 |
|---|
Other
| Other | 2017 International Conference on Computing, Networking and Communications, ICNC 2017 |
|---|---|
| Country | United States |
| City | Silicon Valley |
| Period | 26/01/17 → 29/01/17 |
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SEINA : A stealthy and effective internal attack in Hadoop systems. / Wang, Jiayin; Wang, Teng; Yang, Zhengyu; Mao, Ying; Mi, Ningfang; Sheng, Bo.
2017 International Conference on Computing, Networking and Communications, ICNC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 525-530 7876183 (2017 International Conference on Computing, Networking and Communications, ICNC 2017).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
TY - GEN
T1 - SEINA
T2 - A stealthy and effective internal attack in Hadoop systems
AU - Wang, Jiayin
AU - Wang, Teng
AU - Yang, Zhengyu
AU - Mao, Ying
AU - Mi, Ningfang
AU - Sheng, Bo
PY - 2017/3/10
Y1 - 2017/3/10
N2 - Big data processing frameworks such as Hadoop [1] are now widely adopted, however the security issues in large scale systems have not been well studied yet. Unlike prior work on data privacy and protection, this paper investigates a potential attack from a compromised internal node against the overall system performance. We develop an effective attack launched from the compromised node that can significantly degrade the data processing performance of the cluster without being detected and blacklisted for job execution, also present a mitigation scheme that protects a Hadoop system from such attack. The results of experiments show that this attack greatly slows down the job executions in the native Hadoop system even with some basic defense mechanisms, however, our mitigation schem can keep the whole cluster running efficiently under such attack.
AB - Big data processing frameworks such as Hadoop [1] are now widely adopted, however the security issues in large scale systems have not been well studied yet. Unlike prior work on data privacy and protection, this paper investigates a potential attack from a compromised internal node against the overall system performance. We develop an effective attack launched from the compromised node that can significantly degrade the data processing performance of the cluster without being detected and blacklisted for job execution, also present a mitigation scheme that protects a Hadoop system from such attack. The results of experiments show that this attack greatly slows down the job executions in the native Hadoop system even with some basic defense mechanisms, however, our mitigation schem can keep the whole cluster running efficiently under such attack.
UR - http://www.scopus.com/inward/record.url?scp=85017344891&partnerID=8YFLogxK
U2 - 10.1109/ICCNC.2017.7876183
DO - 10.1109/ICCNC.2017.7876183
M3 - Conference contribution
T3 - 2017 International Conference on Computing, Networking and Communications, ICNC 2017
SP - 525
EP - 530
BT - 2017 International Conference on Computing, Networking and Communications, ICNC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -