Titlebook: Cyber Security Cryptography and Machine Learning; First International Shlomi Dolev,Sachin Lodha Conference proceedings 2017 Springer Inter

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泥土谦卑

AUGUR

A Supervised Auto-Tuning Approach for a Banking Fraud Detection System, multi-objective genetic algorithm..We deployed our solution in a real-world setting of a large national banking group and conducted an in-depth experimental evaluation. We show that the proposed system was able to detect sophisticated frauds, improving Banksealer’s performance of up to 35% in some cases.

landmark

Varieties of Abnormal Behaviourble. This is interesting as the first natural example of a non-reusable FE. We then show how to adapt their construction to obtain reusable FEs. Of independent interest, we show a generic technique for strengthening the notion of reusability achieved by an FE in the random-oracle model.

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chastise

https://doi.org/10.1057/9781137562210ce. Additionally, we perform authorship attribution of pre-segmented text from the Wikia dataset, and show that while this performs better than multi-label learning it requires large amounts of data to be successful.

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constitutional

Classical Linearized Elasticityundaries with reported command and control communications. The presented results validate our approach, achieving an area under the ROC curve of 0.943 and 95 true positives out of the Top 100 ranked instances on the test data set.