Corpus ID: 14811833

A recommender system for efficient discovery of new anomalies in large-scale access logs

@article{Jiang2016ARS,
  title={A recommender system for efficient discovery of new anomalies in large-scale access logs},
  author={Heju Jiang and Scott Algatt and Parvez Ahammad},
  journal={ArXiv},
  year={2016},
  volume={abs/1610.08117}
}
We present a novel, non-standard recommender system for large-scale security policy management(SPM). Our system Helios discovers and recommends unknown and unseen anomalies in large-scale access logs with minimal supervision and no starting information on users and items. Typical recommender systems assume availability of user- and item-related information, but such information is not usually available in access logs. To resolve this problem, we first use discrete categorical labels to… Expand

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