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How AI is Used to Combat Social Engineering Attacks — Part 1
An Analysis of AI Approaches to Counteract URL Phishing
Background: The High Cost of Social Engineering Attacks on Businesses
Social engineering attacks have emerged as the preferred form of a cyber attack by criminals aiming to gain access to finances and data. Cybercriminals employed social engineering attacks in 20% of all data breaches in 2022¹. These attacks are not only common, but they can also be extraordinarily costly, with the average attack resulting in costs of $4.1 million in 2022². In my conversations with leaders at prominent payment service providers, social engineering consistently appears on their radar.
In this two-part series of articles, we explore some of the AI approaches for detecting social engineering attacks. I have selected four papers sourced from papers with code covering machine learning, deep learning, and generative AI approaches. The papers were selected on the basis of having more than 40 stars.
The machine learning approaches will be covered in part 1, and the deep learning and generative approaches will be covered in part 2.
I will delve into some detail concerning these strategies, their advantages, and their limitations…
