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<p>The openness and interconnectivity of Internet of Things (iot) devices expose the systems to threats such as data leakage, device hijacking, and malware infection. Traditional financial management relies on historical data and simple analysis tools. In the context of big data and iot, enterprises need more flexible and accurate financial decision support systems to respond to market changes and optimize resource allocation. The current situation and challenges of Internet of Things (iot) network security were studied and analyzed, and it was proposed to adopt technologies such as data encryption, identity authentication, access control, intrusion detection and prevention to ensure the security of iot data. Next, a financial decision support model based on genetic network algorithms is constructed. By simulating natural selection and genetic mechanisms, data analysis and mining are optimized to handle a large number of variables and adapt to environmental changes. Design a sustainable thermal energy manufacturing system, establish a production simulation model, simplify the power curve to construct an equipment energy consumption model, and monitor energy consumption data in real time to optimize energy utilization. The cybersecurity measures of the Internet of Things have effectively reduced the risk of cyber attacks and ensured the authenticity and integrity of data. Genetic network algorithms demonstrate powerful optimization capabilities in complex data environments, enhancing the accuracy and flexibility of financial decisions. The thermal energy sustainable manufacturing system has achieved a dual improvement in environmental friendliness and economic benefits by optimizing energy utilization and management, providing strong support for the sustainable development of the manufacturing industry. Therefore, by integrating Internet of Things (iot) cybersecurity technology and genetic network algorithms, the safety of the manufacturing production process can be effectively guaranteed, financial decisions can be optimized, and the implementation of sustainable manufacturing can be promoted, opening up new paths for the industry to develop in a more efficient and environmentally friendly direction.</p>

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Internet of things network security enhancing manufacturing financial services based on artificial intelligence and genetic algorithms

  • 期刊论文

  • 发表日期：

    2026年3月19日

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  • Shanshan Wu

摘要

The openness and interconnectivity of Internet of Things (iot) devices expose the systems to threats such as data leakage, device hijacking, and malware infection. Traditional financial management relies on historical data and simple analysis tools. In the context of big data and iot, enterprises need more flexible and accurate financial decision support systems to respond to market changes and optimize resource allocation. The current situation and challenges of Internet of Things (iot) network security were studied and analyzed, and it was proposed to adopt technologies such as data encryption, identity authentication, access control, intrusion detection and prevention to ensure the security of iot data. Next, a financial decision support model based on genetic network algorithms is constructed. By simulating natural selection and genetic mechanisms, data analysis and mining are optimized to handle a large number of variables and adapt to environmental changes. Design a sustainable thermal energy manufacturing system, establish a production simulation model, simplify the power curve to construct an equipment energy consumption model, and monitor energy consumption data in real time to optimize energy utilization. The cybersecurity measures of the Internet of Things have effectively reduced the risk of cyber attacks and ensured the authenticity and integrity of data. Genetic network algorithms demonstrate powerful optimization capabilities in complex data environments, enhancing the accuracy and flexibility of financial decisions. The thermal energy sustainable manufacturing system has achieved a dual improvement in environmental friendliness and economic benefits by optimizing energy utilization and management, providing strong support for the sustainable development of the manufacturing industry. Therefore, by integrating Internet of Things (iot) cybersecurity technology and genetic network algorithms, the safety of the manufacturing production process can be effectively guaranteed, financial decisions can be optimized, and the implementation of sustainable manufacturing can be promoted, opening up new paths for the industry to develop in a more efficient and environmentally friendly direction.