Titlebook: Smart Log Data Analytics; Techniques for Advan Florian Skopik,Markus Wurzenberger,Max Landauer Book 2021 Springer Nature Switzerland AG 202

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Book 2021 parts with a total of 8 chapters that include a detailed view on existing solutions, as well as novel techniques that go far beyond state of the art. The first part of this book motivates the entire topic and highlights major challenges, trends and design criteria for log data analysis approaches,

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AECID: A Light-Weight Log Analysis Approach for Online Anomaly Detection,oresee AECID to be a smart sensor for established SIEM solutions. Parts of AECID are open source and already included in Debian Linux and Ubuntu. This chapter provides vital information on its basic design, deployment scenarios and application cases to support the research community as well as early adopters of the software package.

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novel machine learning approaches.Presents step-by-step exaThis book provides insights into smart ways of computer log data analysis, with the goal of spotting adversarial actions. It is organized into 3 major parts with a total of 8 chapters that include a detailed view on existing solutions, as w

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Survey on Log Clustering Approaches,ally analyzing log data is difficult since it contains massive amounts of unstructured and diverse messages collected from heterogeneous sources. Therefore, several approaches that condense or summarize log data by means of clustering techniques have been proposed. Picking the right approach for a p

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Time Series Analysis for Temporal Anomaly Detection, However, clustering methods only produce static collections of clusters. Therefore, such approaches frequently require a reformation of the clusters in dynamic environments due to changes in technical infrastructure. Moreover, clustering alone is not able to detect anomalies that do not manifest th

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AECID: A Light-Weight Log Analysis Approach for Online Anomaly Detection,ification of events in a network, their correlation, evaluation, and interpretation up to a dynamically-configurable alerting system. Eventually, we foresee AECID to be a smart sensor for established SIEM solutions. Parts of AECID are open source and already included in Debian Linux and Ubuntu. This

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A Concept for a Tree-Based Log Parser Generator,ated. Usually, log data is available in form of unstructured text lines and there exists no common standard for the appearance of logs. Hence, log parsers are required to pre-process log lines and structure their information for further analysis. State of the art log parsers still apply pre-defined