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potential, FL faces critical security, privacy, and performance challenges under practical constraints and considerations. For example, poisioning attacks against FL can heavily impact model performance and
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the incidence of bugs and errors. New technologies and methods will fuse the ever-increasing capabilities of generative AI with techniques such as light-weight sanity and security scanners, model
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the incidence of bugs and errors. New technologies and methods will fuse the ever-increasing capabilities of generative AI with techniques such as light-weight sanity and security scanners, model
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designs as well as the security against attacks on on-device ML. Impact : The outcome of this project will directly contribute to the roadmap of securely developing on-device ML applications and systems
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designs as well as the security against attacks on on-device ML. Impact : The outcome of this project will directly contribute to the roadmap of securely developing on-device ML applications and systems