Title
A Robust Estimator for Evaluating Internet Worm Infection Rate
Abstract
The Internet worm is a menace for the security of the Internet users. To detect and protect the Internet worm becomes an important research topic in the field of Internet security. A robust estimation method for evaluating worm infection rate is proposed in this paper. The robust estimator of worm infection rate is derived based on the robust maximum likelihood estimation principle at first; The corresponding elements of the equivalent weight matrix constructed by the residuals and some chosen weight functions are given; The error influence functions related to the robust estimator and the least squares estimator are respectively analyzed; At last, a simulated example is carried out. It is shown that the robust estimation is effective and reliable in resisting the bad influence of the outlying scan data on the estimated worm infection rate with high computation convergence speed.
Year
DOI
Venue
2007
10.1109/CIS.2007.65
CIS
Keywords
Field
DocType
robustness,computer worms,robust estimator,parameter estimation,maximum likelihood estimate,internet,internet security,packaging,weight function,least squares approximation,security
Convergence (routing),Least squares,Internet security,Computer science,Computer worm,Robust statistics,Robustness (computer science),Estimation theory,Statistics,The Internet
Conference
Volume
Issue
ISBN
null
null
0-7695-3072-9
Citations 
PageRank 
References 
0
0.34
4
Authors
3
Name
Order
Citations
PageRank
Yan Deng100.34
Guanzhong Dai210714.73
Shuxin Chen352.79