Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Characterizing mobile traffic is important to network operators from a network performance and security standpoint. In many cases, such as a performance degradation or security threat, it is useful to know that traffic is being generated by a specific mobile application. Recent methods for identifying mobile traffic have relied on computationally expensive detailed inspection of HTTP flows which may not scale across large networks.  proposes a lightight method to generate a probabilistic model of an application based on a distribution of domain names.  observe that a large portion of mobile applications have traffic to domain names that are critical to how the application functions. Network operators can use this model to verify if a set of one or more domain names is associated with a mobile application during a performance issue or security event. Based on analysis of real mobile network traffic, the model can correctly correlate domain names with associated applications at a rate of 90% in various scenarios. These results show that identifying applications by domain names via this lightight solution is feasible and merits continued future work.
['Wei Wang', 'Jeffrey Bickford']
I am writing a research paper on a idea WhatApp: Modeling mobile applications by domain names
[{"from": "human", "value": "I am writing a research paper on a idea WhatApp: Modeling mobile applications by domain names"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Characterizing mobile traffic is important to network operators from a network performance and security standpoint. In many cases, such as a performance degradation or security threat, it is useful to know that traffic is being generated by a specific mobile application. Recent methods for identifying mobile traffic have relied on computationally expensive detailed inspection of HTTP flows which may not scale across large networks.  proposes a lightight method to generate a probabilistic model of an application based on a distribution of domain names.  observe that a large portion of mobile applications have traffic to domain names that are critical to how the application functions. Network operators can use this model to verify if a set of one or more domain names is associated with a mobile application during a performance issue or security event. Based on analysis of real mobile network traffic, the model can correctly correlate domain names with associated applications at a rate of 90% in various scenarios. These results show that identifying applications by domain names via this lightight solution is feasible and merits continued future work."}]