Paper Info
Title
Preprocessing DNS log data for effective data mining
Abstract
The Domain Name Service (DNS) provides a critical function in directing Internet traffic. Defending DNS servers from bandwidth attacks is assisted by the ability to effectively mine DNS log data for statistical patterns. Processing DNS log data can be classified as a data-intensive problem, and as such presents challenges unique to this class of problem. When problems occur in capturing log data, or when the DNS server experiences an outage (scheduled or unscheduled), the normal pattern of traffic for that server becomes clouded. Simple linear interpolation of the holes in the data does not preserve features such as peaks in traffic (which can occur during an attack, making them of particular interest). We demonstrate a method for estimating values for missing portions of time sensitive DNS log data. This method would be suitable for use with a variety of datasets containing time series values where certain portions are missing.
Year
DOI
Venue
2009
10.1109/ICC.2009.5199359
ICC
Keywords
Field
DocType
data-intensive problem,internet traffic,preprocessing dns log data,log data,time series value,processing dns log data,domain name,dns log data,missing portion,time sensitive dns log,dns server,effective data mining,linear interpolation,time series,statistical analysis,domain name service,interpolation,information science,internet,web server,algorithm design and analysis,computer science,servers,data mining
Data mining,Algorithm design,Computer science,Interpolation,Server,Domain Name System,Computer network,Preprocessor,DNS zone transfer,Internet traffic,Web server
Conference
ISSN
Citations 
PageRank 
1550-3607
6
0.64
References 
Authors
6
3
Name
Order
Citations
PageRank
Mark E. Snyder191.07
Ravi Sundaram276272.13
Mayur Thakur310710.65