Div 7 Seminar - Yu-Shun Wang, Venkatta Pingali, Norihito Fujita

Yu-Shun Wang, Venkata Pingali, and Norihito Fujita
members of the X-Bone project team
Joe Touch, project leader

Thu, June 16
2:00 PM PDT

Extending the X-Bone: Global Deployment and Peer-to-Peer Extensions

The X-Bone is a system for deploying and managing IP overlay networks, composed of IP-in-IP tunnels, which supports virtual topologies, IPsec security, and dynamic routing. This talk presents an update on the X-Bone system, its Virtual Internet Architecture, and extensions to support a persistent global overlay system and to support peer-to-peer use of its IP-level overlays.

The talk is presented in three parts, each 10-15 minutes:

Part I: Overview of the X-Bone and the Virtual Internet Architecture - Yu-Shun Wang, GRA, USC CE Ph.D. candidate

Part II: GX-Bone: Extensions to Support a Persistent Global Overlay System - Venkata Pingali, GRA, USC CS Ph.D. candidate

Part III: Extensions to Support Peer-to-Peer Use of X-Bone Services - Norihito Fujita, Visiting Researcher, NEC Tokyo

Bio

Yu-Shun Wang is a Ph.D. candidate at the Department of Electrical Engineering of USC. His research focuses on network architecture, and security.

Venkata Pingali is a fourth year Ph.D student at USC. He has a BTech from IIT Bombay, India and an MS from University of Utah, and his research focuses on automatic network configuration.

Norihito Fujita is a visiting researcher from NEC Corporation, Japan. He received the B.E. and M.E. degrees in electrical engineering from Kyoto University, Japan. His research focuses on peer-to-peer networks.

C. -C. (Jay) Kuo
EE Department

Thursday, February 10, 2005
11:00 am
11th floor large conference room

On Detecting TCP SYN Flooding Attack

Detection of TCP SYN flooding attack in aggregate traffic has several advantages over the end-node based approaches. The detection scheme consists of two process, observation process and decision process. The observation process uses the protocol behavior of TCP SYN-FIN (RST) pairs to provide some information with the decision process which can decide the occurrence of the attack based on the information after an observation period. However, the observation process suffers the background noises caused by long-lived connections and passive RST packets. To reduce the noise, the normalized residue sequences and partial completion filters (PCF) have been considered in the observation process. In the decision process, cumulative sum (CUSUM) method and a simple anomaly detection using one threshold have been proposed. To achieve more refined detection capability, HMM-based detection scheme is proposed in the decision process. We model the Internet traffic using a hidden Markov model (HMM). Different traffic patterns corresponding to the normal traffic, the low-rate attack and the high-rate attack are used to train them so that we can obtain several different HMMs. The several HMMs are expected to overcome the drawback that the detection scheme using a threshold has some problems caused by low threshold or high threshold. The performance of each combination is evaluated via trace-driven simulations in terms of the detection time and detection probability.

Bio

Dr. C.-C. Jay Kuo received the B.S. degree from the National Taiwan University, Taipei, in 1980 and the M.S. and Ph.D. degrees from the Massachusetts Institute of Technology, Cambridge, in 1985 and 1987, respectively, all in Electrical Engineering. He is with the Department of Electrical Engineering, the Signal and Image Processing Institute (SIPI) and the Integrated Media Systems Center (IMSC) at the University of Southern California (USC) as Professor of Electrical Engineering and Mathematics. His research interests are in the areas of digital media processing, multimedia compression, communication and networking technologies, and embedded multimedia system design. Dr. Kuo is a Fellow of IEEE and SPIE. He received the National Science Foundation Young Investigator Award (NYI) and Presidential Faculty Fellow (PFF) Award in 1992 and 1993, respectively.

Dr. Kuo has guided 58 students to their Ph.D. degrees and supervised 15 postdoctoral research fellows. Currently, his research group at USC consists around 30 Ph.D. students and 5 postdoctors (please visit website http://viola.usc.edu), which is one of the largest academic research groups in multimedia technologies. He is a co-author of more than 700 technical publications in international conferences and journals as well as the following seven books. Dr. Kuo is Editor-in-Chief for the Journal of Visual Communication and Image Representation, and Editor for the Journal of Information Science and Engineering and the RURASIP Journal of Applied Signal Processing. He is also on the Editorial Board of the IEEE Signal Processing Magazine. He served as Associate Editor for IEEE Transactions on Image Processing in 1995-98, IEEE Transactions on Circuits and Systems for Video Technology in 1995-1997 and IEEE Transactions on Speech and Audio Processing in 2001-2003.