Real Time Anomaly Detection in Massive Data Streams with ELK Stack

Jakup Fondaj; Zirije Hasani

doi:10.3844/jcssp.2019.814.823

Real Time Anomaly Detection in Massive Data Streams with ELK Stack

Journal of Computer Science ◽

10.3844/jcssp.2019.814.823 ◽

2019 ◽

Vol 15 (6) ◽

pp. 814-823

Author(s):

Jakup Fondaj ◽

Zirije Hasani

Keyword(s):

Anomaly Detection ◽

Real Time ◽

Data Streams ◽

Massive Data

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Real-Time Sentiment-Based Anomaly Detection in Twitter Data Streams

Advances in Artificial Intelligence - Lecture Notes in Computer Science ◽

10.1007/978-3-319-18356-5_17 ◽

2015 ◽

pp. 196-203

Author(s):

Khantil Patel ◽

Orland Hoeber ◽

Howard J. Hamilton

Keyword(s):

Anomaly Detection ◽

Real Time ◽

Data Streams ◽

Twitter Data

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Towards Real Time Epidemiology: Data Assimilation, Modeling and Anomaly Detection of Health Surveillance Data Streams

Lecture Notes in Computer Science - Intelligence and Security Informatics: Biosurveillance ◽

10.1007/978-3-540-72608-1_8 ◽

2007 ◽

pp. 79-90 ◽

Cited By ~ 7

Author(s):

Luís M. A. Bettencourt ◽

Ruy M. Ribeiro ◽

Gerardo Chowell ◽

Timothy Lant ◽

Carlos Castillo-Chavez

Keyword(s):

Data Assimilation ◽

Anomaly Detection ◽

Real Time ◽

Data Streams ◽

Health Surveillance ◽

Surveillance Data ◽

Epidemiology Data ◽

Health Surveillance Data

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Real-time High Performance Anomaly Detection over Data Streams

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems - DEBS '17 ◽

10.1145/3093742.3095102 ◽

2017 ◽

Cited By ~ 7

Author(s):

Dimitrije Jankov ◽

Sourav Sikdar ◽

Rohan Mukherjee ◽

Kia Teymourian ◽

Chris Jermaine

Keyword(s):

Anomaly Detection ◽

Real Time ◽

Data Streams ◽

High Performance ◽

Performance Anomaly

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Automated Real-Time Classification and Decision Making in Massive Data Streams from Synoptic Sky Surveys

2014 IEEE 10th International Conference on e-Science ◽

10.1109/escience.2014.7 ◽

2014 ◽

Cited By ~ 1

Author(s):

S. George Djorgovski ◽

Ashish Mahabal ◽

Ciro Donalek ◽

Matthew Graham ◽

Andrew Drake ◽

...

Keyword(s):

Decision Making ◽

Real Time ◽

Data Streams ◽

Massive Data ◽

Sky Surveys ◽

Real Time Classification

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Temporal Structure Learning for Clustering Massive Data Streams in Real-Time

Proceedings of the 2011 SIAM International Conference on Data Mining ◽

10.1137/1.9781611972818.57 ◽

2011 ◽

Cited By ~ 7

Author(s):

Michael Hahsler ◽

Margaret H. Dunham

Keyword(s):

Real Time ◽

Data Streams ◽

Structure Learning ◽

Temporal Structure ◽

Massive Data

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Real-time data mining of massive data streams from synoptic sky surveys

Future Generation Computer Systems ◽

10.1016/j.future.2015.10.013 ◽

2016 ◽

Vol 59 ◽

pp. 95-104 ◽

Cited By ~ 11

Author(s):

S.G. Djorgovski ◽

M.J. Graham ◽

C. Donalek ◽

A.A. Mahabal ◽

A.J. Drake ◽

...

Keyword(s):

Data Mining ◽

Real Time ◽

Data Streams ◽

Massive Data ◽

Time Data ◽

Sky Surveys ◽

Real Time Data

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Detecting Insider Threats Using RADISH: A System for Real-Time Anomaly Detection in Heterogeneous Data Streams

IEEE Systems Journal ◽

10.1109/jsyst.2016.2558507 ◽

2017 ◽

Vol 11 (2) ◽

pp. 471-482 ◽

Cited By ~ 26

Author(s):

Brock Bose ◽

Bhargav Avasarala ◽

Srikanta Tirthapura ◽

Yung-Yu Chung ◽

Donald Steiner

Keyword(s):

Anomaly Detection ◽

Real Time ◽

Data Streams ◽

Heterogeneous Data ◽

Insider Threats

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Pipeline for Real-time Anomaly Detection in Log Data Streams using Apache Kafka and Apache Spark

International Journal of Computer Applications ◽

10.5120/ijca2018917942 ◽

2018 ◽

Vol 182 (24) ◽

pp. 8-13 ◽

Cited By ~ 2

Author(s):

Poojitha G. ◽

Sowmyarani C.

Keyword(s):

Anomaly Detection ◽

Real Time ◽

Data Streams ◽

Apache Spark ◽

Log Data

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Real-Time Anomaly Detection from Environmental Data Streams

Lecture Notes in Geoinformation and Cartography - AGILE 2015 ◽

10.1007/978-3-319-16787-9_8 ◽

2015 ◽

pp. 125-144 ◽

Cited By ~ 6

Author(s):

Sergio Trilles ◽

Sven Schade ◽

Óscar Belmonte ◽

Joaquín Huerta

Keyword(s):

Anomaly Detection ◽

Real Time ◽

Data Streams ◽

Environmental Data

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Real-Time Deep Learning-Based Anomaly Detection Approach for Multivariate Data Streams with Apache Flink

10.1007/978-3-030-92231-3_4 ◽

2021 ◽

pp. 39-49

Author(s):

Tae Wook Ha ◽

Jung Mo Kang ◽

Myoung Ho Kim

Keyword(s):

Deep Learning ◽

Anomaly Detection ◽

Real Time ◽

Data Streams ◽

Multivariate Data ◽

Detection Approach

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