On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Empirically derived analytic models of wide-area TCP connections
IEEE/ACM Transactions on Networking (TON)
Wide area traffic: the failure of Poisson modeling
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
Difficulties in simulating the internet
IEEE/ACM Transactions on Networking (TON)
Models and framework for supporting runtime decisions in Web-based systems
ACM Transactions on the Web (TWEB)
NetFence: preventing internet denial of service from inside out
Proceedings of the ACM SIGCOMM 2010 conference
Plug & execute framework for network traffic generation
Proceedings of the Sixth Annual Workshop on Cyber Security and Information Intelligence Research
DTRAB: combating against attacks on encrypted protocols through traffic-feature analysis
IEEE/ACM Transactions on Networking (TON)
Modeling web usage profiles of cloud services for utility cost analysis
Proceedings of the Winter Simulation Conference
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Internet background traffic modeling and simulation is the main challenge when constructing a test environment for network intrusion detection experiments. However, a realistic simulation of network traffic through analytical models is difficult, because the classic distributions are usually ineffective when applied to traffic-related random variables. A modeling and simulation approach using heavy-tailed mixture distributions is introduced in this paper. In the case study, this approach is used to build analytical models for random variables of several major Internet applications (FTP, HTTP, SMTP, POP3, SSH) of a campus network. Several statistical features of an NS2 simulation are compared against those of the traffic traces being simulated. The comparison indicates that the simulation is statistically similar to the real traffic.