NDLI: Eagle: User profile-based anomaly detection for securing Hadoop clusters

Content Provider	IEEE Xplore Digital Library
Author	Gupta, C. Sinha, R. Yong Zhang
Copyright Year	2015
Description	Author affiliation: eBay Inc., San Jose, CA, USA (Gupta, C.; Sinha, R.; Yong Zhang)
Abstract	Existing Big data analytics platforms, such as Hadoop, lack support for user activity monitoring. Several diagnostic tools such as Ganglia, Ambari, and Cloudera Manager are available to monitor health of a cluster, however, they do not provide algorithms to detect security threats or perform user activity monitoring. Hence, there is a need to develop a scalable system that can detect malicious user activities, especially in real-time, so that appropriate actions can be taken against the user. At eBay, we developed such a system named Eagle, which collects audit logs from Hadoop clusters and applications running on them, analyzes users behavior, generates profiles per user of the system, and predicts anomalous user activities based on their prior profiles. Eagle is a highly scalable system, capable of monitoring multiple eBay clusters in real-time. It includes machine-learning algorithms that create user profiles based on the user's history of activities. As far as we know, this is the first activity monitoring system on the Hadoop-ecosystem for the detection of intrusion-related activities using behavior-based profiles of users. When a user performs any operation in the cluster, Eagle matches current user action against his prior activity pattern and raises alarm if it suspects anomalous action. We investigate two machine-learning algorithms: density estimation, and principal component analysis (PCA). In this paper, we introduce the Eagle system, discuss the algorithms in detail, and show performance results. We demonstrate that the sensitivity of the density estimation algorithm is 93%, however the sensitivity of our system increases by 4.94% (on average) to 98% (approximately) by using an ensemble of the two algorithms during anomaly detection.
Starting Page	1336
Ending Page	1343
File Size	334886
Page Count	8
File Format	PDF
e-ISBN	9781479999262
DOI	10.1109/BigData.2015.7363892
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Estimation Hadoop Cluster Anomaly detection Training User profiles Clustering algorithms Machine learning Real-time systems User activity monitoring Monitoring Principal component analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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