USENIX Enigma 2023 - Characterizing and Measuring Misleading and Harmful Online Ad Content at Scale скачать в хорошем качестве

USENIX Enigma 2023 - Characterizing and Measuring Misleading and Harmful Online Ad Content at Scale

USENIX Enigma 2023 - Characterizing and Measuring Misleading and Harmful Online Ad Content at Scale Eric Zeng, Carnegie Mellon University Like it or not, online advertising is a core part of the internet, sustaining many free websites and services. However, it is also a potent vector for abuse; malicious actors can use the infrastructure of ad networks to serve scams, malware, and other misleading content to millions of users. Research on online advertising in the computer security and privacy community tends to focus on privacy and web security issues. However, in this talk I argue that additional research and transparency is needed for the content of online ads, where social engineering techniques and dark patterns are regularly used to mislead users, direct them to scams, and achieve other harmful ends. View the full Enigma 2023 program at https://www.usenix.org/conference/eni...