Is there a R implementation of isolation forest for anomaly detection?
See the iforest package on Sourceforge or on R-Forge:

This package implements an anomaly detection method that detects data-anomalies using binary trees. Using the property that anomalies are more susceptible to isolation, anomalies can be detected as data points which have short expected path lengths.


  Isolation Forest detects data-anomalies using binary trees. Platform:
  R Reference: Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou, “Isolation
  Forest”, IEEE International Conference on Data Mining 2008 (ICDM 08)


or the isofor package on GitHub:

One efficient way of performing outlier detection in high-dimensional datasets is to use random forests. The isofor ‘isolates’ observations by randomly selecting a feature and then randomly selecting a split
value between the maximum and minimum values of the selected feature.