Artificial intelligence(AI)algorithms achieve outstanding results in many applicationdomains such as computer vision and natural language processing The performance ofAl models is the outcome of complex and costly mod...Artificial intelligence(AI)algorithms achieve outstanding results in many applicationdomains such as computer vision and natural language processing The performance ofAl models is the outcome of complex and costly model architecture design and trainingprocesses.Hence,it is paramount for model owners to protect their AI models frompiracy-model cloning,illegitimate distribution and use.IP protection mechanisms havebeen applied to Al models,and in particular to deep neural networks,to verify themodel ownership.State-of-the-art AI model ownership protection techniques have beensurveyed.The pros and cons of Al model ownership protection have been reported.The majonity of previous works are focused on watermarking,while more advancedmethods such fingerprinting and attestation are promising but not yet explored indepth.This study has been concluded by discussing possible research directions in thearea.展开更多
Modern Artificial Intelligence(AI)systems largely rely on advanced algorithms,including machine learning techniques such as deep learning.The research community has invested significant efforts in understanding these ...Modern Artificial Intelligence(AI)systems largely rely on advanced algorithms,including machine learning techniques such as deep learning.The research community has invested significant efforts in understanding these algorithms,optimally tuning them,and improving their performance,but it has mostly neglected the security facet of the problem.Recent attacks and exploits demonstrated that machine learning‐based algorithms are susceptible to attacks targeting computer systems,including backdoors,hardware Trojans and fault attacks,but are also susceptible to a range of attacks specifically targeting them,such as adversarial input perturbations.展开更多
基金supported by the European Union Horizon 2020 research and innovation program under CPSoSAware project(grant no.871738)by Science Foundation Ireland,grant no.12/RC/2289-P2,Insight Centre for Data Analytics。
文摘Artificial intelligence(AI)algorithms achieve outstanding results in many applicationdomains such as computer vision and natural language processing The performance ofAl models is the outcome of complex and costly model architecture design and trainingprocesses.Hence,it is paramount for model owners to protect their AI models frompiracy-model cloning,illegitimate distribution and use.IP protection mechanisms havebeen applied to Al models,and in particular to deep neural networks,to verify themodel ownership.State-of-the-art AI model ownership protection techniques have beensurveyed.The pros and cons of Al model ownership protection have been reported.The majonity of previous works are focused on watermarking,while more advancedmethods such fingerprinting and attestation are promising but not yet explored indepth.This study has been concluded by discussing possible research directions in thearea.
文摘Modern Artificial Intelligence(AI)systems largely rely on advanced algorithms,including machine learning techniques such as deep learning.The research community has invested significant efforts in understanding these algorithms,optimally tuning them,and improving their performance,but it has mostly neglected the security facet of the problem.Recent attacks and exploits demonstrated that machine learning‐based algorithms are susceptible to attacks targeting computer systems,including backdoors,hardware Trojans and fault attacks,but are also susceptible to a range of attacks specifically targeting them,such as adversarial input perturbations.
