Year: 2025
Type: article
Abstract: In the digital era, search engine rankings play a crucial role in shaping online visibility and user engagement. However, fraudulent practices such as search ranking manipulation, click fraud, and SEO poisoning have become increasingly prevalent, compromising the credibility of search results. This project introduces an AI-powered mobile application designed to detect fraudulent search rankings and ensure fair visibility for legitimate content. The system leverages deep learning algorithms and data analytics to identify anomalies in search patterns, traffic sources, and keyword manipulation techniques. By analyzing user behavior, backlink authenticity, and ranking fluctuations, the app effectively distinguishes between organic growth and artificially inflated rankings. The AI model, trained on diverse datasets, continuously adapts to evolving fraudulent strategies, enhancing detection accuracy. The proposed solution empowers businesses, marketers, and search engines to maintain a transparent digital ecosystem, mitigating the impact of ranking fraud and ensuring a trustworthy online search experience.
Authors: Gayathiri V, Rooban Reyeash S, Ashish J
Institution: Madurai Kamaraj University
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410100106