A comparison of algorithms for anomaly detection in safeguards and computer security systems using neural networks
Conference
·
OSTI ID:10167458
Detection of anomalies in nuclear safeguards and computer security systems is a tedious and time-consuming task. It typically requires the examination of large amounts of data for unusual patterns of activity. Neural networks provide a flexible pattern-recognition capability that can easily be adapted for these purposes. In this paper, we discuss architectures for accomplishing this task.
- Research Organization:
- Los Alamos National Lab., NM (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- W-7405-ENG-36
- OSTI ID:
- 10167458
- Report Number(s):
- LA-UR-92-2214; CONF-9207102-27; ON: DE92018637
- Resource Relation:
- Conference: Institute of Nuclear Materials Management (INMM) annual meeting,Orlando, FL (United States),19-22 Jul 1992; Other Information: PBD: [1992]
- Country of Publication:
- United States
- Language:
- English
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