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Towards privacy preserving AI based composition framework in edge networks using fully homomorphic encryption
به سمت حفظ حریم خصوصی و حفظ چارچوب ترکیب مبتنی بر هوش مصنوعی در شبکه های لبه ای با استفاده از رمزنگاری کاملاً همگن-2020 We present a privacy-preserving framework for Artificial Intelligence (AI) enabled composition for the edge
networks. Edge computing is a very promising technology for provisioning realtime AI services due to low
response time and network bandwidth requirements. Due to the lack of computational capabilities, an edge
device alone cannot provide the complex AI services. Complex AI tasks should be divided into multiple subtasks
and distributed among multiple edge devices for efficient service provisioning in the edge network.
AI-enabled or automatic service composition is one of the essential AI tasks in the service provisioning.
In edge computing-based service provisioning, service composition related tasks need to be offloaded to
several edge nodes for efficient service. Edge nodes can be used for monitoring services, storing Qualityof-
Service (QoS) data, and composing services to find the best composite service. Existing service composition
methods use plaintext QoS data. Hence, attackers may compromise edge devices to reveal QoS data of
services and modify them for giving an advantage to particular edge service providers, and the AI-based
service composition becomes biased. From that point of view, a privacy-preserving framework for AI-based
service composition is required for the edge networks. In our proposed framework, we introduce an AI-based
composition model for edge services in the edge networks. Additionally, we present a privacy-preserving
AI service composition framework to perform composition on encrypted QoS data using fully homomorphic
encryption (FHE) algorithm. We conduct several experiments to evaluate the performance of our proposed
privacy-preserving service composition framework using a synthetic QoS dataset. Keywords: Edge-AI | Artificial Intelligence | Privacy in edge networks | Privacy-preserving AI | Privacy-preserving AI-based service | composition | Privacy-preserving service composition |
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