Title
Mining Large Network Reconnaissance Data
Abstract
This paper examines techniques for a large network infrastructure reconnaissance and dives into a real-world case study of a nation-wide passive network vulnerability assessment. The main goal of this study is to understand methods of a large network risk evaluation and conduct practical experiments using a national network. The main contribution of this paper is a non-intrusive method of a large network infrastructure reconnaissance and an application of acquired data to measure network vulnerability exposures within the analysed network. In this study our assumption is based on an estimation that actual threats come from the actively exploited vulnerabilities. Information on exploit-targeted platforms and vulnerabilities could be easily collected from a large set of malicious websites and automatically turned into signatures. We propose an automated method of building such signatures and use those to analyse the reconnaissance data set to identify ranges of vulnerable systems.
Year
DOI
Venue
2013
10.1109/PRDC.2013.38
Dependable Computing
Keywords
Field
DocType
national network,large network risk evaluation,large set,analysed network,reconnaissance data,large network reconnaissance data,network vulnerability exposure,real-world case study,nation-wide passive network vulnerability,acquired data,large network infrastructure reconnaissance,vulnerability assessment,network security,risk analysis
Risk evaluation,Computer science,Vulnerability assessment,Risk analysis (business),Computer security,Passive networks,Network security,Vulnerability management,Vulnerability
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
4
Name
Order
Citations
PageRank
Yarochkin Fyodor1122.22
Yennun Huang2738106.38
Yung-Li Hu383.01
Sy-Yen Kuo42304245.46