An Investigation of Performance Analysis of Anomaly Detection Techniques for Big Data in SCADA Systems
Journal Title: EAI Endorsed Transactions on Industrial Networks and Intelligent Systems - Year 2015, Vol 2, Issue 3
Abstract
Anomaly detection is an important aspect of data mining, where the main objective is to identify anomalous or unusual data from a given dataset. However, there is no formal categorization of application-specific anomaly detection techniques for big data and this ignites a confusion for the data miners. In this paper, we categorise anomaly detection techniques based on nearest neighbours, clustering and statistical approaches and investigate the performance analysis of these techniques in critical infrastructure applications such as SCADA systems. Extensive experimental analysis is conducted to compare representative algorithms from each of the categories using seven benchmark datasets (both real and simulated) in SCADA systems. The effectiveness of the representative algorithms is measured through a number of metrics. We highlighted the set of algorithms that are the best performing for SCADA systems.
Authors and Affiliations
Mohiuddin Ahmed, Adnan Anwar, Abdun Naser Mahmood, Zubair Shah, Michael J. Maher
Keywords
Related Articles
- EP ID EP46025
- DOI http://dx.doi.org/10.4108/inis.2.3.e5
- Views 521
- Downloads 0
Comparison of Different Neural Network Training Algorithms with Application to Face Recognition
Research in the field of face recognition has been popular for several decades. With advances in technology, approaches to solving this problems haves changed. Main goal of this paper was to compare different training al...
Centrality-Based Paper Citation Recommender System
Researchers cite papers in order to connect the new research ideas with previous research. For the purpose of finding suitable papers to cite, researchers spend a considerable amount of time and effort. To help researche...
TiPeNeSS: A Timed Petri Net Simulator Software with Generally Distributed Firing Delays
Performance analysis can be carried out in several ways, especially in case of Markovian models. In order to interpret high level of abstraction, we often use modeling tools like timed Petri nets (TPNs). Although some su...
Applying algorithm finding shortest path in the multiple- weighted graphs to find maximal flow in extended linear multicomodity multicost network
The shortest path finding algorithm is used in many problems on graphs and networks. This article will introduce the algorithm to find the shortest path between two vertices on the extended graph. Next, the algorithm fin...
Wireless Broadband Opportunities through TVWS for Networking in Rural areas of Africa
In this paper, we propose a new approach based on Cognitive Radio technology to address the challenges for ensuring connectivity in remote areas of Africa. Indeed, the current network coverage is concentrated around the...