Name
Title | ||
|---|---|---|
Anomaly intrusion detection for system call using the soundex algorithm and neural networks |
Abstract | ||
|---|---|---|
To improve the anomaly intrusion detection system using system calls, this study focuses on supervisor learning neural networks using the soundex algorithm which is designed to change feature selection and variable length data into a fixed length learning pattern. That is, by changing variable length sequential system call data into a fixed length behavior pattern using the soundex algorithm, this study conducted neural learning by using a backpropagation algorithm. The proposed method and N-gram technique are applied for anomaly intrusion detection of system call using sendmail data of UNM to demonstrate its performance. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ISCC.2005.33 | ISCC |
Keywords | Field | DocType |
n-gram technique,neural networks,fixed length,behavior pattern,system call,backpropagation algorithm,fixed length behavior pattern,backpropagation,length learning pattern,variable length sequential system,variable length sequential system call data,anomaly intrusion detection system,soundex algorithmwhich,variable length data,supervisor learning neural networks,anomaly intrusion detection,feature selection,soundex algorithm,neural nets,security of data,machine learning,automata,data mining,intrusion detection,neural network,computer networks,frequency,databases | Data mining,Feature selection,Computer science,System call,Artificial intelligence,Artificial neural network,Intrusion detection system,Supervisor,Soundex,Pattern recognition,Automaton,Algorithm,Backpropagation | Conference |
ISSN | ISBN | Citations |
1530-1346 | 0-7695-2373-0 | 7 |
PageRank | References | Authors |
0.51 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| ByungRae Cha | 1 | 51 | 14.59 |
| Binod Vaidya | 2 | 232 | 26.75 |
| Seungjo Han | 3 | 63 | 10.87 |