  Denial of service attacks pose a threat in constant growth. This is mainly
due to their tendency to gain in sophistication, ease of implementation,
obfuscation and the recent improvements in occultation of fingerprints. On the
other hand, progress towards self-organizing networks, and the different
techniques involved in their development, such as software-defined networking,
network-function virtualization, artificial intelligence or cloud computing,
facilitates the design of new defensive strategies, more complete, consistent
and able to adapt the defensive deployment to the current status of the
network. In order to contribute to their development, in this paper, the use of
artificial immune systems to mitigate denial of service attacks is proposed.
The approach is based on building networks of distributed sensors suited to the
requirements of the monitored environment. These components are capable of
identifying threats and reacting according to the behavior of the biological
defense mechanisms in human beings. It is accomplished by emulating the
different immune reactions, the establishment of quarantine areas and the
construction of immune memory. For their assessment, experiments with public
domain datasets (KDD'99, CAIDA'07 and CAIDA'08) and simulations on various
network configurations based on traffic samples gathered by the University
Complutense of Madrid and flooding attacks generated by the tool DDoSIM were
performed.
