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

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Human-Machine Decision Support Systems for Insider Threat Detectionithin a dynamic and ever-changing organisation? More recently, there has been interest in how visual analytics can be incorporated with machine-based approaches, to alleviate the data analytics challenges of anomaly detection and to support human reasoning through visual interactive interfaces. Furt

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Dynamic Analysis of Malware Using Run-Time Opcodesd as a means of enhancing the feature set. Feature selection was then investigated to tackle the feature explosion which resulted in more than 100,000 features in some cases. As the earliest detection of malware is the most favourable, run-length, i.e. the number of recorded opcodes in a trace, was

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Big Data Analytics for Intrusion Detection System: Statistical Decision-Making Using Finite Dirichleese data to improve the performance of the decision engine. Finally, the decision engine is designed based on the Dirichlet mixture model with a lower-upper interquartile range as decision engine. The performance of this framework is evaluated on two well-known datasets, the NSL-KDD and UNSW-NB15. T

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Security of Online Examinationsr unauthorized access to sensitive information. In order to prevent such attacks and impersonation threats, we have employed smart techniques of continuous authentication. Therefore, we propose two schemes; Interactive and Secure E-Examination Unit (ISEEU) which is based on video monitoring, and Sma

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Attribute Noise, Classification Technique, and Classification Accuracy data about online credit-card transactions. According to the empirical outcomes, we find that the noise hinders the classification accuracy significantly. In addition, the results indicate that the accuracy of data classification depends on the quality of the data and the used classification techni

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Learning from Loads: An Intelligent System for Decision Support in Identifying Nodal Load Disturbanche overall goal of the intelligent system is to provide a degree of possibility as to whether the load demand is legitimate or it has been manipulated in a way that is a threat to the safety of the node and that of the grid in general. The proposed system is tested with real-world data.

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Visualization and Data Provenance Trends in Decision Support for Cybersecurity Security visualization showing provenance from a spectrum of data samples on an attack helps researchers to reconstruct the attack from source to destination. This helps identify possible attack patterns and behaviors which results in the creation of effective detection mechanisms and cyber-attacks

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Book 2017ises a selection of application-oriented research contributions. The investigations undertaken across these chapters focus on diverse and critical Cybersecurity problems, such as Intrusion Detection, Insider Threats, Insider Threats, Collusion Detection, Run-Time Malware Detection, Intrusion Detecti