Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In cognitive radio networks, an adversary transmits signals whose characteristics emulate those of primary users, in order to prevent secondary users from transmitting. Such an attack is called primary user emulation (PUE) attack. There are two main types of primary users in white space: TV tors and wireless microphones. Existing work on PUE attack detection focused on the first category. Hover, for the latter category, primary users are mobile and their transmission por is low. These unique properties of wireless microphones introduce great challenges and existing methods are not applicable. ,  propose a novel method to detect the PUE attack of mobile primary users.  exploit the correlations beten RF signals and acoustic information to verify the existence of wireless microphones. The effectiveness of our approach is validated through extensive real-world experiments. It shows that our method achieves both false positive rate and false negative rate lor than 0.1.
['Shaxun Chen', 'Kai Zeng', 'Prasant Mohapatra']
I am writing a research paper on a idea Hearing is believing: Detecting mobile primary user emulation attack in white space
[{"from": "human", "value": "I am writing a research paper on a idea Hearing is believing: Detecting mobile primary user emulation attack in white space"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In cognitive radio networks, an adversary transmits signals whose characteristics emulate those of primary users, in order to prevent secondary users from transmitting. Such an attack is called primary user emulation (PUE) attack. There are two main types of primary users in white space: TV tors and wireless microphones. Existing work on PUE attack detection focused on the first category. Hover, for the latter category, primary users are mobile and their transmission por is low. These unique properties of wireless microphones introduce great challenges and existing methods are not applicable. ,  propose a novel method to detect the PUE attack of mobile primary users.  exploit the correlations beten RF signals and acoustic information to verify the existence of wireless microphones. The effectiveness of our approach is validated through extensive real-world experiments. It shows that our method achieves both false positive rate and false negative rate lor than 0.1."}]