Machine learning and social engineering attacks

In my last post I promised to use some real-world use cases from the recent Verizon Data Breach Digest report to illustrate potential ways that machine learning be can used to detect or prevent similar incidents. For my first example, I’ve chosen the case of a manufacturer whose designs for an innovative new model of heavy construction equipment were stolen following a social engineering attack. They were tipped off when a primary competitor, located on another continent, introduced a new piece of equipment that looked like an exact copy of a model recently developed by the victim company. To paraphrase the Verizon report, it went like this. The threat actors identified an employee who they suspected would have access to new product design they were after — the chief design…


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