Secure and Transparent Land Management with AI and Blockchain

Enabling cryptographically enforced access controls for data hosted in untrusted cloud is attractive for many users and organizations. However, designing efficient cryptographically enforced dynamic access control system in the cloud is still challenging. In this paper, we propose Crypt-DAC, a system The rapid increase in textual data in navigation tasks for devices like GPS or smart assistants creates challenges for managing and storing data in large-scale systems. Data deduplication, which reduces storThis project presents AgriSafe, a secure and transparent land registration system designed specifically for the agricultural sector, integrating blockchain and artificial intelligence (AI) technologies. Recognizing the challenges posed by fraud and manipulation in traditional land registration systems, AgriSafe leverages blockchain to ensure immutability and tamper-proof storage of land ownership records. Advanced AI models—including logistic regression, support vector machines, and random forests—are employed to detect and eliminate fraudulent data before it is committed to the blockchain, ensuring only verified land data is stored. The system utilizes smart contracts for automated validation of land data, improving efficiency and accuracy. Furthermore, verified land information is securely stored on the Interplanetary File System (IPFS), with only the data hash stored on the blockchain, ensuring both security and accessibility. AgriSafe undergoes comprehensive evaluation, including AI model accuracy, blockchain scalability, and smart contract vulnerability assessment, delivering a robust, scalable, and fraud-resistant solution for agricultural land registration.age needs by eliminating duplicate data, offers a solution but raises security concerns. This paper introduces DEDUCT, a new method that combines cloud-side and client-side deduplication to achieve high data compression while protecting data privacy. Designed for devices with limited resources, such as IoT devices, DEDUCT includes lightweight preprocessing and safeguards against security risks like side-channel attacks. Testing on a navigation dataset shows that DEDUCT can compress data by up to 66%, significantly cutting storage costs while keeping data secure, making it an efficient choice for managing large-scale data systems.