1.write the title of your project?Neurofuzzy based phishing detection system.2.write the abstract of your base paper?Phishing is the act of attempting to gain access to personal information such as usernames, passwords and bank details by by using a fake website similar to original one. Finding whether a website is genuine or not is largely still a time-consuming manual process of discovering potential phishing sites, verifying if suspicious sites truly are malicious spoofs and if so, distributing their URLs to the appropriate blacklisting services. Attackers increasingly use sophisticated systems for bringing phishing sites up and down rapidly at new locations, making automated response essential. Existing systems use neural network and fuzzy systems alone.In this project, we present a method for rapid detection and analysis of phishing websites. Our method uses historical data from website database sites like phishtank.com and use them to train and test neurofuzzy system. 3. what is the name of your domain?Website security.

4. What are the algorithm used in existing system?Mamdani's fuzzy inference method5.write the exact or approximate result in existing system?When a webpage dataset was given as input the existing system decides whether the given system is genuine or not.6.write the name of tool or tools used in existing system?Fuzzy logic, Matlab7.what is the purpose of your project?To identify whether a website is genuine or not.8.will you implement or simulate your idea?The idea will be simulated using matlab9.write the name of tool or tools used in proposed system?Neurofuzzy logic, Matlab10.what will be the approximate result in proposed system?When a webpage dataset was given as input the existing system decides whether the given system is genuine or not with improved performance..11.what algorithm will be used in proposed system?Back propagation learning algorithm 12.write about the algorithm used in existing system step by step procedure with 1 eg? Step.1 Collect dataset. Step.2 Design fuzzy membership functions. Step.3 Test the testing data.13.write about the algorithm used in proposed system step by step procedure with 1 eg? Step.1 Collect dataset. Step.2 Design fuzzy membership functions and find weights of neural network. Step.3 Train the network using training data. Step.4 Test the testing data.

14.what are the minimum requirement to run your projcect?15.write the disadvantages of existing system collect these details from minimum 10 reference paper in table form?16.write the conclusion in your base paper?17.is your project result based on design,architecture,performance,delay,speed,throughput,security etc?18.what is the input for your project?19.write the step by step process after getting the input?20.is dataset used for your project?21.write the data used in your existing system and proposed system?22.write the algorithm used in existing system and proposed system in flow diagram?