This paper presents a secure IoT framework for authentication and confidentiality using hybrid cryptographic schemes. The proposed model begins by authenticating users and IoT devices, then activates associated IoT devices that send data to the cloud server. To ensure secure transmission of IoT data, the technique combines Elliptic Curve Cryptography (ECC) with Genetic Algorithm (GA) to generate keys. The data is then encrypted using the Advanced Encryption Standard (AES). The model is evaluated based on parameters such as key size, execution time, throughput, and avalanche effect. Experimental results show that the proposed model ensures data authentication and confidentiality against unauthorized access and data exposure. The approach is robust and performs better than state-of-the-art cryptographic algorithms such as DES and RSA. The Internet of Things (IoT) is a fast-growing technology that is revolutionizing various applications across industries. Its adoption has led to improved service quality and productivity. IoT devices have unlocked significant benefits, including heightened security and efficient management. Moreover, IoT has enabled the delivery of services to individuals in remote locations through cloud-based services, further bridging geographical gaps and enhancing accessibility. Consequently, there is a pressing need for improved data security and privacy for individuals and organizations. Numerous approaches have been introduced to tackle data security concerns. Basic encryption techniques have shown limited effectiveness. Nevertheless, researchers have proposed methods such as homomorphic encryption, hybrid techniques, distributive storage, and data concealment to address these challenges. Security challenges such as modifying sensitive data, data privacy breaches, and unauthorized data utilization pose significant obstacles in IoT systems that rely on cloud technology. Cloud-based IoT systems must adhere to various security requirements, including authentication, authorization, non-repudiation, integrity, and confidentiality. The proposed model encompasses a security framework specifically designed for a wide range of applications within the realm of IoT. It utilizes the SHA-512 algorithm to authenticate the user. ECC is employed to generate keys with a smaller size to enhance data security. This key is then subjected to GA to introduce randomness to its value. AES is utilized for data encryption, employing the secret key that ECC and GA have generated. The suggested hybrid algorithm can improve system security more efficiently by addressing key size issues, ultimately reducing computational power.This paper presents a secure IoT framework for authentication and confidentiality using hybrid cryptographic schemes. The proposed model begins by authenticating users and IoT devices, then activates associated IoT devices that send data to the cloud server. To ensure secure transmission of IoT data, the technique combines Elliptic Curve Cryptography (ECC) with Genetic Algorithm (GA) to generate keys. The data is then encrypted using the Advanced Encryption Standard (AES). The model is evaluated based on parameters such as key size, execution time, throughput, and avalanche effect. Experimental results show that the proposed model ensures data authentication and confidentiality against unauthorized access and data exposure. The approach is robust and performs better than state-of-the-art cryptographic algorithms such as DES and RSA. The Internet of Things (IoT) is a fast-growing technology that is revolutionizing various applications across industries. Its adoption has led to improved service quality and productivity. IoT devices have unlocked significant benefits, including heightened security and efficient management. Moreover, IoT has enabled the delivery of services to individuals in remote locations through cloud-based services, further bridging geographical gaps and enhancing accessibility. Consequently, there is a pressing need for improved data security and privacy for individuals and organizations. Numerous approaches have been introduced to tackle data security concerns. Basic encryption techniques have shown limited effectiveness. Nevertheless, researchers have proposed methods such as homomorphic encryption, hybrid techniques, distributive storage, and data concealment to address these challenges. Security challenges such as modifying sensitive data, data privacy breaches, and unauthorized data utilization pose significant obstacles in IoT systems that rely on cloud technology. Cloud-based IoT systems must adhere to various security requirements, including authentication, authorization, non-repudiation, integrity, and confidentiality. The proposed model encompasses a security framework specifically designed for a wide range of applications within the realm of IoT. It utilizes the SHA-512 algorithm to authenticate the user. ECC is employed to generate keys with a smaller size to enhance data security. This key is then subjected to GA to introduce randomness to its value. AES is utilized for data encryption, employing the secret key that ECC and GA have generated. The suggested hybrid algorithm can improve system security more efficiently by addressing key size issues, ultimately reducing computational power.