Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The pervasive usage of mobile devices,  i.e. , smartphones and tablet computers, and their vast amount of sensors represent a plethora of side channels posing a serious threat to the user's privacy and security. ,  propose a new type of side channel which is based on the ambient-light sensor employed in today's mobile devices. While recent advances in this area of research focused on the employed motion sensors and the camera as ll as the sound,  investigate a less obvious source of information leakage, namely the ambient light.  successfully demonstrate that minor tilts and turns of mobile devices cause variations of the ambient-light sensor information. Furthermore,  show that these variations leak enough information to infer a user's personal identification number (PIN) input based on a set of known PINs. Our results clearly show that  are able to determine the correct PIN---out of a set of 50 random PINs---within the first ten guesses about 80% of the time. In contrast, the chance of finding the right PIN by randomly guessing ten PINs would be 20%. Since the data required to perform such an attack can be gathered without any specific permissions or privileges, the presented attack seriously jeopardizes the security and privacy of mobile-device owners.
['Raphael Spreitzer']
I am writing a research paper on a idea PIN Skimming: Exploiting the Ambient-Light Sensor in Mobile Devices
[{"from": "human", "value": "I am writing a research paper on a idea PIN Skimming: Exploiting the Ambient-Light Sensor in Mobile Devices"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The pervasive usage of mobile devices,  i.e. , smartphones and tablet computers, and their vast amount of sensors represent a plethora of side channels posing a serious threat to the user's privacy and security. ,  propose a new type of side channel which is based on the ambient-light sensor employed in today's mobile devices. While recent advances in this area of research focused on the employed motion sensors and the camera as ll as the sound,  investigate a less obvious source of information leakage, namely the ambient light.  successfully demonstrate that minor tilts and turns of mobile devices cause variations of the ambient-light sensor information. Furthermore,  show that these variations leak enough information to infer a user's personal identification number (PIN) input based on a set of known PINs. Our results clearly show that  are able to determine the correct PIN---out of a set of 50 random PINs---within the first ten guesses about 80% of the time. In contrast, the chance of finding the right PIN by randomly guessing ten PINs would be 20%. Since the data required to perform such an attack can be gathered without any specific permissions or privileges, the presented attack seriously jeopardizes the security and privacy of mobile-device owners."}]