An immune intelligent approach for security assurance

Information Security Assurance implies ensuring the integrity, confidentiality and availability of critical assets for an organization. The large amount of events to monitor in a fluid system in terms of topology and variety of new hardware or software, overwhelms monitoring controls. Furthermore, the multi-facets of cyber threats today makes it difficult even for security experts to handle and keep up-to-date. Hence, automatic "intelligent" tools are needed to address these issues. In this paper, we describe a `work in progress' contribution on intelligent based approach to mitigating security threats. The main contribution of this work is an anomaly based IDS model with active response that combines artificial immune systems and swarm intelligence with the SVM classifier. Test results for the NSL-KDD dataset prove the proposed approach can outperform the standard classifier in terms of attack detection rate and false alarm rate, while reducing the number of features in the dataset.