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Extra info for Bio-Inspired Models of Network, Information, and Computing Systems: 7th International ICST Conference, BIONETICS 2012, Lugano, Switzerland, December 10--11, 2012, Revised Selected Papers
6, pp. 671–678. Morgan Kaufmann, San Mateo (1994) 5.
The algorithm is able to quickly react to various load level changes by temporarily modifying the learning parameter’s settings. We show in a set of experiments that using the Reactive ASR-FA signiﬁcantly speeds up the adaptation process of ant routing algorithms and assures lower values of the mean packet delay. It can be also employed in DoS and DDoS attacks detection. Keywords: Adaptive routing 1 · Ant algorithms · Computer networks Introduction Many similarities can be found between swarms of insects and parallel, distributed information systems that are controlled in a decentralized manner.
Thus, in this case the best results can be obtained by modifying the learning rate ψ. Figure 7 (right) shows how the DDoS attack can be detected by analyzing the averaged value of the Anderson–Darling statistic. There is a high peak on the plot after the attack starts. It can be seen that also the end of the attack is visible as a second peak on the plot. The DDoS attack can be easily detected when using the Reactive ASR-FA algorithm, as it implies a change in the network conditions. 7 47 50 40 30 20 10 0 0 500 1000 1500 2000 Simulation Time [s] Fig.