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Paper Type
ERF
Abstract
The automation of the industrial paradigms characterizes the era of Industry 4.0. The implementation nuances involve data and model sharing among allies and partners working on the same domain. Privacy and security of data and models are fundamental necessities that must be satisfied for this protocol's proper functioning. To this end, we propose a conceptual and algorithmic framework of a model obfuscation scheme. It is built upon the extant data obfuscation paradigm. The future work lies with the implementation and establishment of its viability. This research is expected to develop into deployable model obfuscation technique which practitioners from the industrial domain can adopt.
Paper Number
1130
Recommended Citation
Sadhukhan, Payel; Chakraborty, Tanujit; and Sengupta, Kausik, "Deploying model obfuscation: towards the privacy of decision-making models on shared platforms" (2024). AMCIS 2024 Proceedings. 38.
https://aisel.aisnet.org/amcis2024/security/security/38
Deploying model obfuscation: towards the privacy of decision-making models on shared platforms
The automation of the industrial paradigms characterizes the era of Industry 4.0. The implementation nuances involve data and model sharing among allies and partners working on the same domain. Privacy and security of data and models are fundamental necessities that must be satisfied for this protocol's proper functioning. To this end, we propose a conceptual and algorithmic framework of a model obfuscation scheme. It is built upon the extant data obfuscation paradigm. The future work lies with the implementation and establishment of its viability. This research is expected to develop into deployable model obfuscation technique which practitioners from the industrial domain can adopt.
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