Privacy-Guarding Optimal Route Finding with Support for Semantic Search on Encrypted Graph in Cloud Computing Scenario

Wu, Bin; Chen, Xianyi; Wu, Zongda; Zhao, Zhiqiang; Mei, Zhuolin; Zhang, Caicai

doi:10.1155/2021/6617959

Cited by 9 publications

(4 citation statements)

References 35 publications

(67 reference statements)

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“…So more useful content understanding technologies are necessary to be introduced into our recommendation scenario to pursue higher recommendation performances. Third, privacy concern often exists in user-related decision systems [45][46][47][48][49]. And how to secure sensitive user information during recommendations is another research direction in our future study.…”

Section: Conclusion and Further Discussionmentioning

confidence: 95%

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Liu¹,

Wan²,

Yan³

2023

Computer Modeling in Engineering &Amp; Sciences

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With the popularity of 5G and the rapid development of mobile terminals, an endless stream of short video software exists. Browsing short-form mobile video in fragmented time has become the mainstream of user's life. Hence, designing an efficient short video recommendation method has become important for major network platforms to attract users and satisfy their requirements. Nevertheless, the explosive growth of data leads to the low efficiency of the algorithm, which fails to distill users' points of interest on one hand effectively. On the other hand, integrating user preferences and the content of items urgently intensify the requirements for platform recommendation. In this paper, we propose a collaborative filtering algorithm, integrating time context information and user context, which pours attention into expanding and discovering user interest. In the first place, we introduce the temporal context information into the typical collaborative filtering algorithm, and leverage the popularity penalty function to weight the similarity between recommended short videos and the historical short videos. There remains one more point. We also introduce the user situation into the traditional collaborative filtering recommendation algorithm, considering the context information of users in the generation recommendation stage, and weight the recommended short-form videos of candidates. At last, a diverse approach is used to generate a Top-K recommendation list for users. And through a case study, we illustrate the accuracy and diversity of the proposed method.

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Section: Conclusion and Further Discussionmentioning

confidence: 95%

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Liu¹,

Wan²,

Yan³

2023

Computer Modeling in Engineering &Amp; Sciences

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“…Wu et al [42] first used homomorphic encryption function in compressed sensing data collection, and proposed an efficient data collection method with privacy protection to prevent traffic analysis and tracking in wireless sensor networks. Liuet al [43] propose a neural network algorithm of gated recurrent unit based on FL, where FL is a privacypreserving machine learning technology named federated learning.…”

Section: Privacy Protection In Traffic Flow Datamentioning

confidence: 99%

LSH-based missing value prediction for abnormal traffic sensors with privacy protection in edge computing

Gao

Liu

Miao

2023

Complex Intell. Syst.

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Traffic flow prediction is an important part of intelligent transportation systems (ITS). However, sensor failures or the transmission distortion often occur in the process of data acquisition, which will inevitably cause the loss or abnormality of traffic flow data transmitted to the edge server. In this situation, it is necessary to share traffic flow data among different platforms. However, existing traffic flow prediction methods are facing two challenges in the process of traffic flow data sharing. First, user privacy is often leaked in the process of sharing traffic data on various platforms. Moreover, with the continuous updating of data, the efficiency and scalability of data sharing between different platforms will become lower and lower. In view of the above challenges, in this paper, we propose a novel prediction method for the missing traffic flow data caused by abnormal sensors, named $$ASMVP_{distr-LSH}$$ A S M V P d i s t r - L S H based on distributed locality-sensitive hashing (LSH) technique. At last, a case study is presented to illustrate the feasibility and effectiveness of our approach $$ASMVP_{distr-LSH}$$ A S M V P d i s t r - L S H .

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“…An improved algorithm was proposed to maintain the shortest paths between all pairs of vertices in a dynamic graph [15]. In addition, Liu C [16], Ghosh E [17], Sun F [18], and Wu B [19] described their research on this topic. However, these works neglect privacy protection.…”

Section: Introductionmentioning

confidence: 99%

A Swell Neural Network Algorithm for Solving Time-Varying Path Query Problems with Privacy Protection

Zhao

2024

Electronics

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In this paper, a swell neural network (SNN) algorithm was proposed for solving time-varying path query (TVPQ) problems with privacy protection with the following goals: (i) querying the K-nearest paths with time limitations in a time-varying scenario, and (ii) protecting private information from neighborhood attacks. The proposed SNN is a network in which the optimal paths can be calculated at the same time with no need for training. For TVPQ, a node is considered a neuron, and time-varying means that an edge has different costs in different time windows. For SNN, the query paths are swell sets from the start to the target within an upper limit. An encrypted index is designed for privacy protection. The evaluation of the efficiency and accuracy of the SNN was carried out based on New York road instances.

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Privacy-Guarding Optimal Route Finding with Support for Semantic Search on Encrypted Graph in Cloud Computing Scenario

Cited by 9 publications

References 35 publications

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

LSH-based missing value prediction for abnormal traffic sensors with privacy protection in edge computing

A Swell Neural Network Algorithm for Solving Time-Varying Path Query Problems with Privacy Protection

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