Machine Learning Driven Social Engineering

Given at the 10th Annual Chicago Hacking Conference on 11/6/23. Machine learning (ML) is arguably the most potent advancement in technology since atomic fission with similar benefit and risk extremes. The outcome driven nature of machine learning allows computers to rapidly test theories to find pathways to support specific goals. These approaches applied to social engineering can be used to manipulate human factors for purposes including cybersecurity breach. This session will cover the philosophies, strategies and tactics used to accomplish a successful campaign to recruit human assets to a cause. Factors to mitigate risk in these advanced social engineering attacks will also be examined.

People > Machines (Part Three)

Computer scientists love the idea of artificial intelligence (AI). It is the centerpiece of many mainstream science fiction works. It’s also a preferred buzzword of lazy vendors and marketers. Until computers can convince (trick) a reasonable human being that they are living beings (Turing test) all claims of AI are misleading at best. In this installment, I won’t debunk the types of claims of AI. We will examine the difference between how computers and humans think and the implications of the differences.

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