Improving hidden Markov model inferences with private data from multiple observers
Date
2012
Authors
Nguyen, H.
Roughan, M.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
IEEE Signal Processing Letters, 2012; 19(10):696-699
Statement of Responsibility
Hung X. Nguyen and Matthew Roughan
Conference Name
Abstract
Most large attacks on the Internet are distributed. As a result, such attacks are only partially observed by any one Internet Service Provider (ISP). Detection would be significantly easier with pooled observations, but privacy concerns often limit the information that providers are willing to share. Multi-party secure distributed computation provides a means for combining observations without compromising privacy. In this letter, we show the benefits of this approach, the most notable of which is that combinations of observations solve identifiability problems in existing approaches for detecting network attacks.
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
© 2012 IEEE