[PDF][PDF] Artificial intelligence and intrusion detection: Current and future directions
J Frank - Proceedings of the 17th national computer security …, 1994 - engineering.iastate.edu
Abstract Intrusion Detection systems (IDSs) have previously been built by hand. These
systems have di culty successfully classifying intruders, and require a significant amount of …
systems have di culty successfully classifying intruders, and require a significant amount of …
A framework for constructing features and models for intrusion detection systems
Intrusion detection (ID) is an important component of infrastructure protection mechanisms.
Intrusion detection systems (IDSs) need to be accurate, adaptive, and extensible. Given …
Intrusion detection systems (IDSs) need to be accurate, adaptive, and extensible. Given …
Data mining-based intrusion detectors: An overview of the columbia ids project
The field of Intrusion Detection has been an active area of research for some time. The goal
of an Intrusion Detection System (IDS) is to provide another layer of defense against …
of an Intrusion Detection System (IDS) is to provide another layer of defense against …
[PDF][PDF] Data mining techniques for (network) intrusion detection systems
T Lappas, K Pelechrinis - … of Computer Science and Engineering UC …, 2007 - Citeseer
In Information Security, intrusion detection is the act of detecting actions that attempt to
compromise the confidentiality, integrity or availability of a resource. Intrusion detection does …
compromise the confidentiality, integrity or availability of a resource. Intrusion detection does …
[PDF][PDF] A scalable clustering technique for intrusion signature recognition
N Ye, X Li - Proceedings of the 2001 IEEE workshop on information …, 2001 - Citeseer
Clustering and Classification Algorithm–Supervised (CCA-S), which we developed for
detecting intrusions into computer network systems for intrusion detection. CCA-S is used to …
detecting intrusions into computer network systems for intrusion detection. CCA-S is used to …
Decision tree classifier for network intrusion detection with GA-based feature selection
Machine Learning techniques such as Genetic Algorithms and Decision Trees have been
applied to the field of intrusion detection for more than a decade. Machine Learning …
applied to the field of intrusion detection for more than a decade. Machine Learning …
Network intrusion detection signature analysis using decision graphs
TE Bernhard, SD Shanklin, GS Lathem - US Patent 6,609,205, 2003 - Google Patents
“Use of A Taxonomy of Security Faults.” T. Aslam, et al., pp. 1-10,(found at http://www. cs.
purdue. edu/coast/archive/data/categ24. html), Sep. 1996.“Artificial Intelligence and Intrusion …
purdue. edu/coast/archive/data/categ24. html), Sep. 1996.“Artificial Intelligence and Intrusion …
A data mining framework for building intrusion detection models
There is often the need to update an installed intrusion detection system (IDS) due to new
attack methods or upgraded computing environments. Since many current IDSs are …
attack methods or upgraded computing environments. Since many current IDSs are …
[图书][B] A data mining framework for constructing features and models for intrusion detection systems
W Lee - 1999 - search.proquest.com
Intrusion detection is an essential component of critical infrastructure protection
mechanisms. The traditional pure “knowledge engineering” process of building Intrusion …
mechanisms. The traditional pure “knowledge engineering” process of building Intrusion …
[HTML][HTML] An expert system application for network intrusion detection
KA Jackson, DH DuBois… - Proceedings of the 14th …, 1991 - books.google.com
This paper describes the design of a prototype intrusion detection system for the Los Alamos
National Laboratory's Integrated Computing Network (ICN). The Network Anomaly Detection …
National Laboratory's Integrated Computing Network (ICN). The Network Anomaly Detection …