By Malgorzata Gadomska, Andrzej Pacut (auth.), Mario Giacobini (eds.)

This ebook constitutes the refereed joint lawsuits of 7 workshops on evolutionary computing, EvoWorkshops 2007, held in Valencia, Spain in April 2007.

The fifty five revised complete papers and 24 revised brief papers provided have been rigorously reviewed and chosen from a complete of a hundred and sixty submissions. in response to the seven workshops lined, the papers are equipped in topical sections on evolutionary computation in communications, networks, and attached platforms; evolutionary computation in finance and economics; evolutionary computation in picture research and sign processing; interactive evolution and humanized computational intelligence; evolutionary tune and paintings; evolutionary algorithms in stochastic and dynamic environments; in addition to evolutionary computation in transportation and logistics.

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In this work, we extend the approach to explicitly incorporate feedback from the anomaly detector. Moreover, previous instances of evolved attacks were designed within the context of a virtual vulnerability and verified against the Snort signature based detector post training [5,6]. Conversely, this work provides attacks that are specific to a real application vulnerability under the more advanced behavioral anomaly detection paradigm. To do so, evolution is guided towards attacks that are able to make use of unforeseen weaknesses in the detector, thus M.

SCIENCE, 5(7), 867-872, 2004. 12. N. Zhang, B. Karp, S. Floyd, L. Peterson, “RR-TCP: A reordering-robust TCP with DSACK”, Tech. Rep. TR-02-006, ICSI, Berkeley, CA Evolving Buffer Overflow Attacks with Detector Feedback H. Gunes Kayacik, Malcolm I. Heywood, and A. Nur Zincir-Heywood Faculty of Computer Science, Dalhousie University 6050 University Avenue. Halifax. NS. ca Abstract. A mimicry attack is an exploit in which basic behavioral objectives of a minimalist ’core’ attack are used to design multiple attacks achieving the same objective from the same application.

Dorigo and G. di Caro, “AntNet: Distributed Stigmergetic Control for Communications Networks”, Journal of Artirtificial Intelligence Research 9, 317-365, 1998. 7. A. Pacut, M. Gadomska, A. Igielski, “Ant-Routing vs. Q-Routing in Telecommunication Networks”, Proceedings of the 20-th ECMS Conference, 2006. 8. R. Schoonderwoerd, O. Holland, J. Bruten, and L. Rothkrantz, “Ant-based load balancing in telecommunications networks”, Adaptive Behavior, 5(2), 169-207, 1996. 9. W. R. Stevens, “TCP/IP Illustrated, Volume I, II”, Addison-Wesley, 1994.

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