Recent researches showed that DNA encoding and pattern matching can be used for the intrusion-detection system (IDS), with results of high rate of attack detection. The evaluation of these intrusion detection systems is based on datasets that are generated decades ago. However, numerous studies outlined that these datasets neither inclusively reflect the network traffic, nor the modern low footprint attacks, and do not cover the current network threat environment. In this paper, a new DNA encoding for misuse IDS based on UNSW-NB15 dataset is proposed. The proposed system is performed by building a DNA encoding for all values of 49 attributes. Then attack keys (based on attack signatures) are extracted and, finally, Raita algorithm is applied to classify records, either attacks or normal, based on the extracted keys. The results of the current experiment showed that the proposed system achieved good detection rates for all of attacks, which included the Analysis, Backdoor, DoS, Exploits, Fuzzers, Generic, Reconnaissance, Shellcode, and Worms, with values of 82.56%, 92.68%, 75.59%, 75.42%, 67%, 99.28%, 81.02%, 73.6%, 85%, and 90.91%, respectively. The values of false alarm rate and accuracy were equal to 24% and 89.05%, respectively. Also, the execution time for the proposed system was found to be short, where the values of the encoding time and matching time for one record were 0.45 and 0.002 second, respectively.
