|Domain – Java Project – Cloud Computing – Secure Computing|
Frequent itemset mining, a predominant mining technique and an essential operation in association rule mining which is considered as one of the most widely used data mining techniques on massive datasets nowadays. With the huge increase on the scale of datasets (With the introduction of Social networks) collected and stored with cloud services in recent years, it is very important to carry out this computation-intensive mining process in the cloud. Amount of work also transferred the approximate mining computation into the exact computation, where such methods not only improve the accuracy also aim to enhance the efficiency. However, while mining data stored on public clouds, it inevitably introduces privacy concerns on sensitive datasets.In this project, we propose a new innovative framework for enforcing privacy in frequent itemset mining, where data will be collected and mined in an encrypted form in a public cloud service. This project is specifically designed with three secure frequent itemset mining protocols on top of this framework. To guarantee data privacy and computation efficiency, we adopt two different homomorphic encryption schemes and design a secure and effective comparison scheme. Our first protocol/condition achieves more efficient mining performance while our second protocol/condition provides a stronger privacy guarantee. In order to further optimize the performance of the second protocol, we leverage a minor trade-off of privacy to get our third condition/protocol to be acheived. Finally, we evaluate the performance of our protocols techniques with extensive experiments, and the results demonstrate that our protocols obviously outperform previous solutions in performance with a similar security level.
• System : Pentium i3 Processor
• Hard Disk : 500 GB.
• Monitor : 15’’ LED
• Input Devices : Keyboard, Mouse
• Ram : 2 GB
• Operating system : Windows 10.
• Coding Language : Java
• Tool : Netbeans 8.2
• Database : MYSQL