Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With the rapid growth of big-data applications, advanced data processing technologies, e.g., machine learning, are widely adopted in many industry fields. Although these technologies demonstrate porful data analyzing and processing capability, there exist some security concerns that may potentially expose the user/owner of the services to information safety risk. In particular, the adoption of neuromorphic computing systems that implement neural network and machine learning algorithms on hardware generates the need for protecting the data security in such systems. ,  introduce the security concerns in the learning-based applications and propose a secured neuromorphic system design that can prevent potential attackers from replicating the learning model. Our results show that the computation accuracy of the designed neuromorphic computing system will quickly degrade when no proper authorization is given, by leveraging the drifting effect of the memristor device.
['Beiye Liu', 'Chaofei Yang', 'Hai Li', 'Yiran Chen', 'Qing Wu', 'Mark Barnell']
I am writing a research paper on a idea Security of neuromorphic systems: Challenges and solutions
[{"from": "human", "value": "I am writing a research paper on a idea Security of neuromorphic systems: Challenges and solutions"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With the rapid growth of big-data applications, advanced data processing technologies, e.g., machine learning, are widely adopted in many industry fields. Although these technologies demonstrate porful data analyzing and processing capability, there exist some security concerns that may potentially expose the user/owner of the services to information safety risk. In particular, the adoption of neuromorphic computing systems that implement neural network and machine learning algorithms on hardware generates the need for protecting the data security in such systems. ,  introduce the security concerns in the learning-based applications and propose a secured neuromorphic system design that can prevent potential attackers from replicating the learning model. Our results show that the computation accuracy of the designed neuromorphic computing system will quickly degrade when no proper authorization is given, by leveraging the drifting effect of the memristor device."}]