  In the authors' opinion, anomaly detection systems, or ADS, seem to be the
most perspective direction in the subject of attack detection, because these
systems can detect, among others, the unknown (zero-day) attacks. To detect
anomalies, the authors propose to use machine synesthesia. In this case,
machine synesthesia is understood as an interface that allows using image
classification algorithms in the problem of detecting network anomalies, making
it possible to use non-specialized image detection methods that have recently
been widely and actively developed. The proposed approach is that the network
traffic data is "projected" into the image. It can be seen from the
experimental results that the proposed method for detecting anomalies shows
high results in the detection of attacks. On a large sample, the value of the
complex efficiency indicator reaches 97%.
