Name
Abstract | ||
|---|---|---|
A machine learning method for remote operation system recognition through their detection signatures with support vector machine (SNM) is proposed. A vector space model of Nmap fingerprint database and techniques for translating the host responses to SVM input vectors are also suggested. Experimental result on identification of signatures in the fingerprint database of Nmap 4.90RC1 but not known for Nmap 4.76 show that our method is effective in the discovery of new signatures not included in current fingerprint database. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/FCST.2009.21 | FCST |
Keywords | DocType | ISBN |
Nmap 4.90RC1,SVM input vectors,vector space model,learning (artificial intelligence),operating systems (computers),new signature,host response,detection signatures,svm input vector,support vector machine,Nmap fingerprint database,current fingerprint database,fingerprint database,digital signatures,detection signature,OS fingerprint,machine learning,signature identification,OS detection,support vector machines,remote operation system detection,Nmap 4.76,nmap fingerprint database | Conference | 978-1-4244-5467-9 |
Citations | PageRank | References |
1 | 0.37 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bofeng Zhang | 1 | 179 | 41.38 |
| Tiezheng Zou | 2 | 1 | 0.37 |
| Yongjun Wang | 3 | 27 | 9.19 |
| Baokang Zhang | 4 | 1 | 0.37 |