Abstract
Today, the Internet of Things is one of the most popular technologies having a significant impact on various aspects of our lives, including social, commercial and economic spheres. In the areas of automation, productivity and comfort, IoT offers tremendous promise for improving the quality of life, being applied in education, smart cities and other areas. However, cyber-attacks and threats pose a serious challenge to smart applications in IoT environments. The presented work investigates the privacy and security issues in the Internet of Things (IoT). The paper analyzes various security techniques, focusing on machine learning, including Naive Bayes, Random Forest and Logistic Regression, and their application to detect anomalies and attacks in IoT networks. The article emphasizes the importance of integrating advanced technologies and ethical principles to create reliable and secure IoT systems.