Statistical-based Anomaly Detection (First stage detection)
PCA-based Multivariate Statistical Network Monitoring for Anomaly Detection
... tivariate statistical monitoring procedure to an industrial pro- cess or a communication network, some appropriate variables need to be measured on that process or ...
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Representing Statistical Network-Based Anomaly Detection by Using Trust
... 57 3.3 Predictability Trust In addition to the types of trust in Section 3.2, this research employed Predictability Trust (PRT) for ADS systems to evaluate a node with multiple statistical characteristics and to ...
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Statistical Approaches for Network Anomaly Detection
... Holt-Winters Forecasting is a algorithm that builds upon expo- nential smoothing which is described in [27]. The specific im- plementation of Holt-Winters Forecasting is described in [12]. We selected this Holt-Winters ...
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Statistical wavelet based anomaly detection in big data with compressive sensing
... Keywords: Anomaly detection; Big data; Through-wall human detection; Compressive sensing 1 Introduction Anomaly detection refers to finding inconsistency with the desired pattern in ...
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Statistical wavelet-based anomaly detection in big data with compressive sensing
... of anomaly data ...the anomaly detection during a signal recovery procedure based on the modified BP reconstruction ...of anomaly and energy consumption, an im- provement was made by ...
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Network Anomaly Detection Based on Statistical Approach and Time Series Analysis
... traffic anomaly such as router rate change, device restart or the worm ...early detection of unusual anomaly in the network is a key to fast recover and avoidance of future serious problem to provide ...
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Adaptive Sampling and Statistical Inference for Anomaly Detection
... We consider a server cluster wherein software-based sensors embedded within the IT infrastruc- ture measure various performance-related parameters associated with the cluster. These measure- ments include ...
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A New Statistical Approach to Network Anomaly Detection
... an anomaly based network intrusion detection system, which detects anomalies using sta- tistical characterizations of the TCP ...same detection rate of first order models, with almost one half ...
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PCA Based Anomaly Detection
... outlier detection methods have been proposed [1], [2], [5], [10], [11], [12], [13], [14], ...density based methods. Statistical approaches [1], [11] assume that the data follows some standard or ...
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Semi-supervised Statistical Approach for Network Anomaly Detection
... good detection results for specified well-known ...drawback. Anomaly-based systems, rely on models of normal behavior of the protected target, any deviation from this model is considered as ...
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VoIP Anomaly Detection - selected methods of statistical analysis
... factor, anomaly detection, self-similarity, long-range ...INTRODUCTION Statistical analysis of network traffic measurements shows a clear presence of the fractal or self-similar properties in com- ...
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Statistical Techniques for Online Anomaly Detection in Data Centers
... of anomaly detection we first quantize the metric being measured and discretize it to a few ...perform anomaly detection for each ...threshold based on an acceptable false negative ...
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Anomaly Detection and Prevention in Network Traffic based on Statistical approach and α Stable Model
... and anomaly detection are extensively used to understand and characterize network traffic behavior, as well as to identify abnormal operational conditions such as malicious ...and anomaly ...
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Anomaly detection of web-based attacks
... the anomaly detection models, the system operates in two different phases, training and ...a statistical model describing normal behavior. The detection phase is where the new request ...
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Softwarization of SCADA: Lightweight Statistical SDN-Agents for Anomaly Detection
... In a scenario where the communication between the In- dustrial Automation and Control Systems (IACS) components uses SDN, the SCADA system could host an IDS application. The control layer of a SDN architecture ...
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An integrated anomaly intrusion detection scheme using statistical,hybridized
... mining based anomaly detection (DMAD), particularly classification methods, have been incessantly enhanced in differentiating normal and attack ...accuracy, detection, and false alarms are not ...
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Botnet Detection based on System and Community Anomaly Detection
... a statistical analysis of the measurements to show that, although not perfectly secure, compressed sensing grants some level of security that comes at almost zero cost and thus may benefit resource-limited ...
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Statistical Inference and α Stable Modeling for Anomaly Detection in Network Traffic
... Fig. 2. Distribution of injected versus synthetic anomalous patterns One of the primary tasks of network administrators is monitoring routers and switches for anomalous traffic behavior such as outages, configuration ...
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IDBSCAN Algorithm Based Proficient Anomaly Detection
... widespread anomaly detection framework named Holmes for regular activities in ...outlier detection system on the basis of ...cluster. Based on the above factor the normal and abnormal point ...
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An Empirical Evaluation of Entropy-based Anomaly Detection
... the anomaly detection ...wavelet detection and heuristic-threshold detection, both of which are described in Section ...each detection method simple to run, and through the labeling of ...
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