[图书][B] Machine learning techniques for the computer security domain of anomaly detection
TD Lane - 2000 - search.proquest.com
In this dissertation, we examine the machine learning issues raised by the domain of
anomaly detection for computer security. The anomaly detection task is to recognize the …
anomaly detection for computer security. The anomaly detection task is to recognize the …
An empirical study of two approaches to sequence learning for anomaly detection
T Lane, CE Brodley - Machine learning, 2003 - Springer
This paper introduces the computer security domain of anomaly detection and formulates it
as a machine learning task on temporal sequence data. In this domain, the goal is to …
as a machine learning task on temporal sequence data. In this domain, the goal is to …
Temporal sequence learning and data reduction for anomaly detection
T Lane, CE Brodley - ACM Transactions on Information and System …, 1999 - dl.acm.org
The anomaly-detection problem can be formulated as one of learning to characterize the
behaviors of an individual, system, or network in terms of temporal sequences of discrete …
behaviors of an individual, system, or network in terms of temporal sequences of discrete …
Detecting the abnormal: Machine learning in computer security
T Lane, CE Brodley - 1997 - docs.lib.purdue.edu
TINOpr oblems of importance in computer security are to I) detect the presence of an intruder
masquerading as the valid user and 2) detect the perpetration of abusive actions on the part …
masquerading as the valid user and 2) detect the perpetration of abusive actions on the part …
[PDF][PDF] Effective Anomaly Detection with Scarce Training Data.
Learning-based anomaly detection has proven to be an effective black-box technique for
detecting unknown attacks. However, the effectiveness of this technique crucially depends …
detecting unknown attacks. However, the effectiveness of this technique crucially depends …
A machine learning approach to anomaly detection
PK Chan, MV Mahoney, MH Arshad - 2003 - repository.fit.edu
Much of the intrusion detection research focuses on signature (misuse) detection, where
models are built to recognize known attacks. However, signature detection, by its nature …
models are built to recognize known attacks. However, signature detection, by its nature …
Learning rules and clusters for anomaly detection in network traffic
PK Chan, MV Mahoney, MH Arshad - Managing Cyber Threats: Issues …, 2005 - Springer
Much of the intrusion detection research focuses on signature (misuse) detection, where
models are built to recognize known attacks. However, signature detection, by its nature …
models are built to recognize known attacks. However, signature detection, by its nature …
[PDF][PDF] Hidden markov models for human/computer interface modeling
T Lane - Proceedings of the IJCAI-99 Workshop on Learning …, 1999 - cerias.purdue.edu
Automated modeling of human behaviors is useful in the computer security domain of
anomaly detection. In the user modeling facet of the anomaly detection domain, the task is to …
anomaly detection. In the user modeling facet of the anomaly detection domain, the task is to …
[图书][B] Practical machine learning: a new look at anomaly detection
T Dunning, E Friedman - 2014 - books.google.com
Finding Data Anomalies You Didn't Know to Look For Anomaly detection is the detective
work of machine learning: finding the unusual, catching the fraud, discovering strange …
work of machine learning: finding the unusual, catching the fraud, discovering strange …
[PDF][PDF] An application of machine learning to anomaly detection
T Lane, CE Brodley - … of the 20th national information systems …, 1997 - coast.cs.purdue.edu
The anomaly detection problem has been widely studied in the computer security literature.
In this paper we present a machine learning approach to anomaly detection. Our system …
In this paper we present a machine learning approach to anomaly detection. Our system …