Online dating insider alpha index
The key challenges facing the insider threat detection and prediction system include unbounded patterns, uneven time lags between activities, data nonstationarity, individuality, collusion attacks, high false alarm rates, class imbalance problem, undetected insider attacks, uncertainty, and the large number of free parameters in the model.To identify the best-to-date insider threat detection and prediction algorithms, our meta-analysis study excludes theoretical papers proposing conceptual algorithms from the 37 selected papers resulting in the selection of 13 papers.
Damage to data integrity can often cause more serious problems than confidentiality breaches.
These insiders have knowledge of the internal workings of the organization, and full possession of all the rights and privileges required to mount an attack that outsiders lack.
Consequently, insiders can make their attacks look like normal operations.
A loss of system availability can paralyse a company.
This can lead to higher costs, lost revenue and reputational damage.
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In order to optimize these conflicting requirements we need to develop an insider threat detection and prediction algorithm (IDPA) that minimizes both false negatives and false positives.