PrivBV: Distance-aware encoding for distributed data with local differential privacy

Sun, Lin; Ping, Guolou; Yao, Xiaojun

doi:10.26599/tst.2021.9010027

Cited by 13 publications

(9 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to solve the location privacy leakage problem in LBS, various methods for environments both in free space and road network have been proposed, such as K-anonymity [12][13][14][15][16][17][18] , local differential privacy [19][20][21][22][23][24][25][26][27] , geo-indistinguishability 10,11,[28][29][30][31][32][33][34][35][36] , and location semantics [37][38][39][40][41][42][43][44][45] . Marco Gruteser et al introduced the concept of K-anonymity in relational databases into the field of privacy protection of location-based services and proposed the location K-anonymity model 12 .…”

Section: Related Workmentioning

confidence: 99%

“…Hong et al 25 investigated the problem of collecting locations of individual users under LDP and proposed the square mechanism to collect the geospatial data by reducing the MSE of each location. Sun et al 26 used LDP for distance estimation between distributed data. The LDP-based location collection and protection methods prevent the location privacy of users from being compromised by data collectors and potential attackers.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Perturb and optimize users’ location privacy using geo-indistinguishability and location semantics

Yan

Mahmood

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Location-based services (LBS) are capable of providing location-based information retrieval, traffic navigation, entertainment services, emergency rescues, and several similar services primarily on the premise of the geographic location of users or mobile devices. However, in the process of introducing a new user experience, it is also easy to expose users’ specific location which can result in more private information leakage. Hence, the protection of location privacy remains one of the critical issues of the location-based services. Moreover, the areas where humans work and live have different location semantics and sensitivities according to their different social functions. Although the privacy protection of a user’s real location can be achieved by the perturbation algorithm, the attackers may employ the semantics information of the perturbed location to infer a user’s real location semantics in an attempt to spy on a user’s privacy to certain extent. In order to mitigate the above semantics inference attack, and further improve the quality of the location-based services, this paper hereby proposes a user side location perturbation and optimization algorithm based on geo-indistinguishability and location semantics. The perturbation area satisfying geo-indistinguishability is thus generated according to the planar Laplace mechanism and optimized by combining the semantics information and time characteristics of the location. The optimum perturbed location that is able to satisfy the minimum loss of location-based service quality is selected via a linear programming method, and can be employed to replace the real location of the user so as to prevent the leakage of the privacy. Experimental comparison of the actual road network and location semantics dataset manifests that the proposed method reduces approximately 37% perturbation distance in contrast to the other state-of-the-art methods, maintains considerably lower similarity of location semantics, and improves region counting query accuracy by a margin of around 40%.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Perturb and optimize users’ location privacy using geo-indistinguishability and location semantics

Yan

Mahmood

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…In [43], local differential privacy (LDP), which offers high-level privacy protections, has recently been adopted as the de facto norm for data sharing and analysis. The primary goal of LDP-based techniques is to extract statistical data about the entire population from sensitive data.…”

Section: Related Workmentioning

confidence: 99%

Novel Hybrid Fusion-Based Technique for Securing Medical Images

Abdallah

Ateya

2022

Electronics

View full text Add to dashboard Cite

The security of images has gained great interest in modern communication systems. This is due to the massive critical applications that are based on images. Medical imaging is at the top of these applications. However, the rising number of heterogenous attacks push toward the development of securing algorithms and methods for imaging systems. To this end, this work considers developing a novel authentication, intellectual property protection, ownership, and security technique for imaging systems, mainly for medical imaging. The developed algorithm includes two security modules for safeguarding various picture kinds. The first unit is accomplished by applying watermarking authentication in the frequency domain. The singular value decomposition (SVD) is performed for the host image’s discrete cosine transform (DCT) coefficients. The singular values (S) are divided into 64 × 64 non-overlapping blocks, followed by embedding the watermark in each block to be robust to any attack. The second unit is made up of two encryption layers to provide double-layer security to the watermarked image. The double random phase encryption (DRPE) and chaotic encryption have been tested and examined in the encryption unit. The suggested approach is resistant to common image processing attacks, including rotation, cropping, and adding Gaussian noise, according to the findings of the experiments. The encryption of watermarked images in the spatial and DCT domains and fused watermarked images in the DCT domain are all discussed. The transparency and security of the method are assessed using various measurements. The proposed approach achieves high-quality reconstructed watermarks and high security by using encryption to images and achieves robustness against any obstructive attacks. The developed hybrid algorithm recovers the watermark even in the presence of an attack with a correlation near 0.8.

show abstract

“…Unfortunately, the strategy also has some downsides: (1) The sparse interaction data and imprecise similarity method lead to limited recommendation effect. In addition, when faced with frequently updated data [4][5][6][7], the prediction efficiency of collaborative filtering is relatively low. (2) Content-based similarity measurement relies on a host of annotation data and does not necessarily reflect the similarity perceived by users, which greatly reduces the personalized effect of video recommendation.…”

Section: Introductionmentioning

confidence: 99%

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Liu¹,

Wan²,

Yan³

2023

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

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.

show abstract

PrivBV: Distance-aware encoding for distributed data with local differential privacy

Cited by 13 publications

References 15 publications

Perturb and optimize users’ location privacy using geo-indistinguishability and location semantics

Perturb and optimize users’ location privacy using geo-indistinguishability and location semantics

Novel Hybrid Fusion-Based Technique for Securing Medical Images

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

Contact Info

Product

Resources

About