Detecting Random and/or Algorithmically-Generated Character Sequences in Domain Names

A method, comprising:

• at a computing platform comprising at least one processor, a communication interface, and memory:
• receiving a seed string and a set of domains to be analyzed in connection with the seed string;
• applying a classification algorithm to the seed string and the set of domains to produce a classification result by:
• calculating similarity scores for domain segments in the set of domains in view of seed segments in the seed string;
• preliminarily classifying each domain segment based on its corresponding similarity score;
• inputting domain segments preliminarily classified as random into a machine learning model to obtain a prediction score;
• and
• determining, based on the similarity score and the prediction score, whether a given domain is classified as random or not-random;
• and
• storing, by the at least one processor, the classification result.

One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, a communication interface, and memory, cause the computing platform to:

• receive a seed string and a set of domains to be analyzed in connection with the seed string;
• apply a classification algorithm to the seed string and the set of domains to product a classification result by:
• calculating similarity scores for domain segments in the set of domains in view of seed segments in the seed string;
• preliminarily classifying each domain segment based on its corresponding similarity score;
• inputting domain segments preliminarily classified as random into a machine learning model to obtain a prediction score;
• and
• determining, based on the similarity score and the prediction score, whether a given domain is classified as random or not-random;
• and
• store the classification result.