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Over the years social network data has been mined to predict individuals' traits such as intelligence and sexual orientation. While mining social network data can provide many beneficial services to the user such as personalized experiences, it can also harm the user when used in making critical decisions such as employment. In this work, we investigate the reliability of applying data mining techniques...
Behavioral pattern prediction has many applications, ranging from consumer buying behavior analysis, web surfing prediction to network attack prediction. The traditional behavioral prediction technique works mainly on a fixed dataset. But recent advances in digital technology generates a huge amount of data which contributes to data stream. Data evolves over time due to the concept drift. Stream-based...
Insider threat detection requires the identification of rare anomalies in contexts where evolving behaviors tend to mask such anomalies. This paper proposes and tests an ensemble-based stream mining algorithm based on supervised learning that addresses this challenge by maintaining an evolving collection of multiple models to classify dynamic data streams of unbounded length. The result is a classifier...
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