RETRACTED ARTICLE: Artificial intelligence assisted cyber threat assessment and applications for the tourism industry

Today, artificial intelligence (AI) can be found in nearly every aspect of travel and tourism, from personalization and recommendation systems to robotics to conversational systems to intelligent travel agents to forecasting and prediction tools and systems for language translation. As a result, this study examines the connection between large-scale big data analysis and smart tourism, resulting in a massive data platform for forecasting and providing feedback on smart tourist developments.This article aims to shed light on the importance of AI in the travel and tourism sector. Many cybersecurity firms are stepping to raise their efforts using artificial intelligence to attain this goal because effective information security is necessary for better detection.An intelligent all-area-advanced tourism cloud platform is demonstrated in this paper, as well as how to design the overall system framework, system structure, and database systems needed to integrate all of the province's tourism resources into a single information resource sharing system.Furthermore, this paper presents an intelligent decision-support system based on big data to reimagine tourism public administration and service. It moreover examines the ramifications of this decision-making mode and implementation procedures. This study covers the framework operation's elements, environment features, and promotion mode by creating a tourism public management and service framework based on big data. Big data-driven decision-support and management can overhaul tourism public management and service models. Cyber threat intelligence and applications, including those that defend systems, networks, programs, devices, and data from cyber threats, could significantly impact this tourism industry.The present tourism industry's problem-solving efficiency, quality, and services have increased. The simulation evaluation can promote the public tourism service in sustainable tourism development with an improved decision accuracy of 97.21%.