Titlebook: Data Analytics and Decision Support for Cybersecurity; Trends, Methodologie Iván Palomares Carrascosa,Harsha Kumara Kalutarage Book 2017 Sp

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Reem Wagdy Moustafa Kamel Abd El-Raoofification depends on various aspects. Though the data classification technique has a major impact on classification accuracy, the nature of the data also matters lot. One of the main concerns that can hinder the classification accuracy is the availability of noise. Therefore, both choosing the appro

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https://doi.org/10.1007/978-981-19-1376-1data to regulate power flow, shape demand with a plethora of pieces of information and ensure reliability at all times. However, the extensive use of information technologies in the power system may also form a Trojan horse for cyberattacks. Smart power systems where information is utilized to predi

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https://doi.org/10.1007/978-3-030-58035-3for cybersecurity. Current analytical time taken to identify zero-day attacks and respond with a patch or detection mechanism is unmeasurable. This is a current challenge and struggle for cybersecurity researchers. User- and data provenance-centric approaches are the growing trend in aiding defensiv

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A Toolset for Intrusion and Insider Threat Detectionork that aims to support IT security experts with identifying novel or obfuscated attacks in company networks, irrespective of their origin inside or outside the company network. A new toolset for anomaly based network intrusion detection is proposed. This toolset uses flow-based data which can be e

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Human-Machine Decision Support Systems for Insider Threat Detectionvileged access and knowledge, are already in a position of great responsibility for contributing towards the security and operations of the organisation. Should an individual choose to exploit this privilege, perhaps due to disgruntlement or external coercion from a competitor, then the potential im

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