DESIGN AND DEVELOPMENT OF AN ATTACK-RESISTANT IOT CLOUD CONVERGENCE ALGORITHM USING ATTRIBUTE-BASED ENCRYPTION

Abstract

As the number of Internet of Things (IoT) devices grows quickly, it becomes harder to keep data handling and communication safe in cloud settings.  This paper describes how an attack-proof IoT cloud convergence method was designed and built. It uses Ciphertext-Policy Attribute-Based Encryption (CP-ABE) to provide strong security and fine-grained, attribute-based access control.  The suggested framework uses CP-ABE based on the Bethencourt-Sahai-Waters (BSW) method to make key generation, sharing, encryption, and decoding safe and user-attribute-aligned. This makes sure that only authorised users can access critical data.  To make sure the encryption is strong and works well, the method uses the JPBC library to perform pairing-based cryptography processes. Using attribute-based registration and login, the user module makes sure that users are who they say they are and that they have the right permissions.  The system handles files by encrypting them with lightweight AES for privacy, hashing them with SHA-256 for integrity checks, and letting you securely share and download files with reporting support.  The Third Party Auditor (TPA) tool also makes sure that files are real and manages user termination to stop people from getting in without permission after a key has been compromised or a characteristic has been changed. A performance study shows that the suggested method works by comparing how much time and memory are used for decrypting both insourced and outsourced files of different sizes.  The results show that the system strikes a good balance between security and speed. This means that it can be used in real-life IoT-cloud situations where resources are limited and changing access control is important.  The comparison study shows that attribute-based encryption is better at protecting against different types of threats while still having a reasonable amount of extra work to do.