Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The Nearby-Friend Problem for a user in the context of location based services is to learn the location of a nearby-friend only if (s)he is actually nearby, while simultaneously maintaining the privacy of their respective locations. The existing works address the problem for two users only. ,  present for the first time a solution which caters to multiple users.  use techniques from Euclidean plane geometry and graph theory to develop a secure multi-party computation approach towards solving the nearby-friend problem efficiently for many users. Our solution ensures users' location privacy by enforcing $k$-anonymity.
['Shashwat Raizada', 'Goutam Paul', 'Vineet Pandey']
I am writing a research paper on a idea Nearby-Friend Discovery Protocol for Multiple Users
[{"from": "human", "value": "I am writing a research paper on a idea Nearby-Friend Discovery Protocol for Multiple Users"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The Nearby-Friend Problem for a user in the context of location based services is to learn the location of a nearby-friend only if (s)he is actually nearby, while simultaneously maintaining the privacy of their respective locations. The existing works address the problem for two users only. ,  present for the first time a solution which caters to multiple users.  use techniques from Euclidean plane geometry and graph theory to develop a secure multi-party computation approach towards solving the nearby-friend problem efficiently for many users. Our solution ensures users' location privacy by enforcing $k$-anonymity."}]