Abstract
The significance of dark patterns is to deceive consumers when they are exploring the internet. There were social networking sites such as LinkedIn, Facebook, and others, where users discovered dark patterns whose goal was to steal users’ personal information or get them to click on advertisements. Dark patterns are created by using the domains such as UI/UX. Although, there many kinds in which they trap the users’ attention to focus though the advertisements on the websites where users can be trapped and may lose their money. There are a few security concerns that are required to detect the dark patterns through smart dark pattern detection. The intended theme proposed in this case is designing the application through which browsing could be done where any dark pattern advertisement is identified that could be alerted through a dialog box. For detection, a novel dark pattern detection approach is designed and considered as in-built application activity. The performance and accuracy are the main factors that judge the intended theme is designed as per the expectations.
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Raju, S.H., Waris, S.F., Adinarayna, S., Jadala, V.C., Rao, G.S. (2022). Smart Dark Pattern Detection: Making Aware of Misleading Patterns Through the Intended App. In: Shakya, S., Balas, V.E., Kamolphiwong, S., Du, KL. (eds) Sentimental Analysis and Deep Learning. Advances in Intelligent Systems and Computing, vol 1408. Springer, Singapore. https://doi.org/10.1007/978-981-16-5157-1_72
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