Title
Detection of interest flooding attacks in Named Data Networking using hypothesis testing
Abstract
With the rapid growth of Internet traffic, new emerging network architectures are under deployment. Those architectures will substitute the current IP/TCP network only if they can ensure better security. Currently, the most advanced proposal for future Internet architecture is Named Data Networking (NDN). However, new computer network architectures bring new types of attacks. This paper focuses on the detection against Interest flooding - one of the most threatening attacks in NDN. The statistical detection is studied within the framework of hypothesis testing. First, we address the case in which all traffic parameters are known. In this context, the optimal test is designed and its statistical performance is given. This allows providing an upper bound on the highest detection accuracy one can expect. Then, a linear parametric model is proposed to estimate unknown parameters and to design a practical test for which the statistical performance is also provided. Numerical results show the relevance of the proposed methodology.
Year
DOI
Venue
2015
10.1109/WIFS.2015.7368571
2015 IEEE International Workshop on Information Forensics and Security (WIFS)
Keywords
Field
DocType
Network security,Named Data Networking,Interest flooding,Statistical detection,Hypothesis testing
Internet security,Content based networking,Computer security,Computer science,Computer network,Dynamic circuit network,Flooding (psychology),Statistical hypothesis testing,The Internet
Conference
ISSN
Citations 
PageRank 
2157-4766
5
0.42
References 
Authors
13
4
Name
Order
Citations
PageRank
Tan N. Nguyen1212.03
Rémi Cogranne254530.57
Guillaume Doyen39813.25
Florent Retraint424622.82