Source: logdata-anomaly-miner
Section: misc
Priority: extra
Maintainer: Roman Fiedler <roman.fiedler@ait.ac.at>
Build-Depends: debhelper (>= 9.0.0), docbook-xsl, docbook-xml, xsltproc
Standards-Version: 3.9.7
Homepage: https://launchpad.net/logdata-anomaly-miner/
Vcs-Git: https://git.launchpad.net/logdata-anomaly-miner
Vcs-Browser: https://git.launchpad.net/logdata-anomaly-miner/tree/

Package: logdata-anomaly-miner
Architecture: all
Depends: python2.6 | python2.7, python-tz, ${misc:Depends}
Suggests: python-scipy
Description: logdata-anomaly-miner allows to create log analysis
  pipelines to analyze log data streams and detect violations
  or anomalies in it. It can be run from console, as daemon with
  e-mail alerting or embedded as library into own programs. It
  was designed to run the analysis with limited resources and
  lowest possible permissions to make it suitable for production
  server use. Analysis methods include:
  .
  * static check patterns similar to logcheck but with extended
    syntax and options.
  * detection of new data elements (IPs, user names, MAC addresses)
  * statistical anomalies in log line values and frequencies
  * correlation rules between log lines as described in th AECID
    approach http://dx.doi.org/10.1016/j.cose.2014.09.006
  .
  The tool is suitable to replace logcheck but also to operate
  as a sensor feeding a SIEM.
  .
  Please report bugs at https://bugs.launchpad.net/logdata-anomaly-miner/+filebug
