Titlebook: Handbook of Big Data Analytics and Forensics; Kim-Kwang Raymond Choo,Ali Dehghantanha Book 2022 Springer Nature Switzerland AG 2022 cyber

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G. Schellong,U. Creutzig,J. Ritterount of the fraudulent transaction can be less than the normal transactions, the impact of a single fraud transaction can be huge in terms of financial loss. Therefore, it is crucial for banks and other financial institutions to be able to detect fraud transactions more effectively. Machine learning

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Therapie der arteriellen Hypertonieentify Advanced Persistent Threats (APT) groups for future risk mitigation by both business and government. Multiple vendors like McAfee and Kaspersky periodically release reports on these APT groups that are absorbed by the security analysts worldwide. These reports identify the Tactics, Techniques

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New Results in Coronary Angioscopy,g decisions. However, there are concerns about these systems being biased towards a certain population or group. The scalable fair clustering algorithm is one of the variants of the disparate notion of fairness to the clustering problem. It solves this problem by ensuring that each cluster has an ap

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Cyber Threat Attribution with Multi-View Heuristic Analysis,can help attribute the malware to its source with higher accuracy. The experiment uses a multi-view approach similar to a recent work that implements a Fuzzy Consensus Clustering Model for threat attribution. Our experiment is conducted with 3594 malware samples corresponding to 12 different APT gro

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Security of Industrial Cyberspace: Fair Clustering with Linear Time Approximation,subsets called fairlets, maintaining the fairness and the K-median objective. In the second phase, these fairlets are merged using an existing K-median algorithm. The time take for the fairlet decomposition here depends on the first phase and it is super-quadratic in relation to the number of input

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