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The combination of sixth-generation (6G) wireless communication technology and the Internet of Things (IoT) is transforming the landscape of digital ecosystems across the world by supporting ultrareliable low-latency communication (URLLC), massive machine-type communications (mMTC), and enhanced mobile broadband (eMBB). Such an evolution enables transformative real-time applications in smart cities, industrial automation, healthcare, and immersive virtual environments. However, as the number of autonomously swapping data on billions of interconnected devices reaches astronomical proportions, the cybersecurity and privacy risks skyrocket. The traditional centralized security systems and cryptographic methods like Advanced Encryption Standard (AES) and Rivest–Shamir–Adleman (RSA) encryption cannot provide the performance, scalability, and resilience demanded by the next-generation networks. The evolving and decentralized structure of the 6G-IoT requires a new paradigm of cybersecurity infrastructure, utilizing advanced encryption technology, artificial intelligence (AI), and blockchain technologies. This chapter examines the weakness of traditional encryption in ultralow-latency settings and reviews ongoing cryptographic developments such as post-quantum cryptography (PQC), lightweight cryptographic algorithms, homomorphic encryption (HE), and secure multicomputation (SMPC). It discusses how blockchain helps improve data integrity, device authentication, and decentralized access control in distributed networks. The conversation extends to AI-driven threat detection frameworks, deep learning (DL), reinforcement learning (RL), federated learning (FL), and collaborative intrusion detection systems (IDS), security analytics that are adaptable, scalable, and privacy-preserving. Focused on the proliferation of cyber-physical systems, this chapter strives to achieve a coherent security strategy that ensures confidentiality, real-time threat intelligence, and dispersed trust. By analyzing such technologies as blockchain-mediated federated AI training, smart contract-based access control, and pipelines of secure communication enhanced with encryption, it proposes an integration-risk-mitigation-agile-security-framework fit for critical 6G-IoT applications. The chapter continues to contextualize the role of compliance mechanisms such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). It emphasizes the necessity of building systems in line with global privacy standards.