BYOD TRUST MODEL USING BLOCKCHAIN TECHNOLOGY

SOFTWARE 1. Programming language : python / Java 2. Blockchain : etherium solidity 3. Dummy database : SQL 4. Interface : PhP framework 5. API : postman 6. Machine learning : random forest MODULE 1. User trust model 2. Device trust model 3. Information trust model 4. Malware detection 5. Evidence collection IMPORTANT NOTES 1. All trust model information will not be stored in the database. It will be store in the blockchain 2. The first block will be created by the master device but block added later can be created by any device that in the trust model 3. The decision to allow or deny user and device access will be calculated by the blockchain PoW. 4. For device trust model it will check if the device have updated antivirus if yes it will not scan the device but if not it will pass the work to malware detection module 6. For malware detection, a malware database will be link to the system and a calculation to set the malware threshold will be done. it will use random forest machine learning 7. No agent or software will be install inside user device. 8. All document in the dummy database will be link to the blockchain using hash number. The document block will also store the document security setting based on Bell-Lapadula Model. This security setting are set by the owner in the initial phase when storing the document in the database. 9. Whenever user access or modify the document, the hash number of the document will be change and will be tight to the user so whatever the flow of the document (email, save to phone, copy) will be recorded and tight to the specific user. This is to differentiate between the original document with the modified document by specific user. DELIVERABLE 1. Trust Model algorithm 2. Trust model flow chart 3. BYOD Trust model system 4. Video tutorial on installing related software 5. Video tutorial on installing the system and how to use the system 6. Video tutorial on how to link the system with the database 7. Video tutorial on how the malware detection tool function 8. Full report of the system 9. Source code