An Optimization Framework for Privacy-preserving Access Control in Cloud-Fog Computing Systems
An Optimization Framework for Privacy-preserving Access Control in Cloud-Fog Computing Systems
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DOI：
10.1109/vtc2020-fall49728.2020.9348516
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发表时间：
2020-11
期刊：
影响因子：
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通讯作者：
Yili Jiang;Kuan Zhang;Y. Qian;Liang Zhou
中科院分区：
文献类型：
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作者：
Yili Jiang;Kuan Zhang;Y. Qian;Liang Zhou
基于云的物联网（IoT）已被应用于支持各种应用之间无处不在的数据收集和集中的数据处理。半可信云拥有强大的资源，能够通过发起推理攻击来推断私有信息。同态加密（HE）是一种有效的方法来保护隐私免受推理攻击，同时允许一定的计算密文。然而，由于额外的通信和计算开销，HE导致更长的延迟。针对云雾计算环境下的隐私保护访问控制问题，提出了一种优化框架.优化目标是最大化系统中的平均用户满意度，其中成本和延迟是衡量用户满意度的关键指标。由于制定的问题的NP-困难，我们提出了一个低复杂度的次优算法来解决它，在访问卸载决策，用户合作，和资源分配考虑。仿真结果表明，我们提出的算法的平均USI（用户满意度指数）和零USI的用户数方面的优势。
The cloud-based Internet-of-Things (IoT) has been applied to support ubiquitous data collection and centralized data processing among various applications. Equipped with powerful resources, a semi-trusted cloud is able to deduce private information by launching inference attack. Homomorphic Encryption (HE) has been proposed as an effective way to preserve privacy from inference attack while allowing certain computation over ciphertext. However, HE leads to longer latency due to additional communication and computation overheads. In this paper, we propose an optimization framework in privacy-preserving access control under cloud-fog computing systems. The optimization goal is to maximize the average user satisfaction in the system, where cost and latency serve as key metrics measuring user satisfaction. Due to the NP-hardness of the formulated problem, we propose a low-complexity suboptimal algorithm to solve it, where the access offloading decision making, user cooperation, and resource allocation are considered. Simulation results are presented to show the advantages of our proposed algorithm in terms of the average USI (User Satisfaction Index) and the number of users with zero USI.