Symbolic dynamic analysis of complex systems for anomaly detection
نویسنده
چکیده
This paper presents a novel concept of anomaly detection in complex dynamical systems using tools of Symbolic Dynamics, Finite State Automata, and Pattern Recognition, where time-series data of the observed variables on the fast time-scale are analyzed at slow time-scale epochs for early detection of (possible) anomalies. The concept of anomaly detection in dynamical systems is elucidated based on experimental data that have been generated from an active electronic circuit with a slowly varying dissipation parameter. ? 2004 Elsevier B.V. All rights reserved.
منابع مشابه
Moving dispersion method for statistical anomaly detection in intrusion detection systems
A unified method for statistical anomaly detection in intrusion detection systems is theoretically introduced. It is based on estimating a dispersion measure of numerical or symbolic data on successive moving windows in time and finding the times when a relative change of the dispersion measure is significant. Appropriate dispersion measures, relative differences, moving windows, as well as tec...
متن کاملDynamic anomaly detection by using incremental approximate PCA in AODV-based MANETs
Mobile Ad-hoc Networks (MANETs) by contrast of other networks have more vulnerability because of having nature properties such as dynamic topology and no infrastructure. Therefore, a considerable challenge for these networks, is a method expansion that to be able to specify anomalies with high accuracy at network dynamic topology alternation. In this paper, two methods proposed for dynamic anom...
متن کاملSymbolic time series analysis for anomaly detection: A comparative evaluation
Recent literature has reported a novel method for anomaly detection in complex dynamical systems, which relies on symbolic time series analysis and is built upon the principles of automata theory and pattern recognition. This paper compares the performance of this symbolic-dynamics-based method with that of other existing pattern recognition techniques from the perspectives of early detection o...
متن کاملSymbolic time series analysis via wavelet-based partitioning
Symbolic time series analysis (STSA) of complex systems for anomaly detection has been recently introduced in literature. An important feature of the STSA method is extraction of relevant information, imbedded in the measured time series data, to generate symbol sequences. This paper presents a wavelet-based partitioning approach for symbol generation, instead of the currently practiced method ...
متن کاملAnomaly detection in thermal pulse combustors using symbolic time series analysis
This paper presents symbolic time series analysis of observable process variables for anomaly detection in thermal pulse combustors. The anomaly detection method has been tested on the time series data of pressure oscillations, generated from a non-linear dynamic model of a generic thermal pulse combustor. Results are presented to exemplify early detection of combustion instability due to reduc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Signal Processing
دوره 84 شماره
صفحات -
تاریخ انتشار 2004