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    IoT DATA PRIVACY AND SECURITY BASED ON BLOCKCHAIN TECHNOLOGY
    (2024-02) Alibadi, Mohammed Talib Raheem
    The integration of Deep Extreme Learning Machine (D.E.L.M.) and blockchain innovation speaks to a worldview move in tending to security and protection challenges inside the Internet of Things (IoT), especially in smart framework situations. This study, about proposes a blockchain-based smart framework that D.E.L.M. moves forward to reinforce security, maximize vitality proficiency, and offer individualized client encounters. The decentralized characteristic of blockchain guarantees data capacity that's safe to alter, thus diminishing the vulnerabilities connected to centralized confirmation frameworks. Factual measurements evaluate the system's execution amid the preparation and approval stages. The framework performs well, with few wrong expectations and tall exactness. This contributes to progressing the understanding of blockchain and D.E.L.M. synergies within the setting of keen frameworks, advertising an establishment for encouraging investigation and advancement inside IoT environments. As smart frameworks become progressively predominant, the proposed framework lays the basis for a more secure, versatile, and privacy-conscious IoT scene.