scholarly journals KPDR : An Effective Method of Privacy Protection

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zihao Shen ◽  
Wei Zhen ◽  
Pengfei Li ◽  
Hui Wang ◽  
Kun Liu ◽  
...  
Keyword(s):  
Private Information ◽  
Privacy Protection ◽  
Graph Model ◽  
Communication Overhead ◽  
Relationship Matrix ◽  
Private Information Retrieval ◽  
Retrieval Model ◽  
User Privacy ◽  
Target Information ◽  
The Relationship

To solve the problem of user privacy disclosure caused by attacks on anonymous areas in spatial generalization privacy protection methods, a K and P Dirichlet Retrieval (KPDR) method based on k-anonymity mechanism is proposed. First, the Dirichlet graph model is introduced, the same kind of information points is analyzed by using the characteristics of Dirichlet graph, and the anonymous set of users is generated and sent to LBS server. Second, the relationship matrix is generated, and the proximity relationship between the user position and the target information point is obtained by calculation. Then, the private information retrieval model is applied to ensure the privacy of users’ target information points. Finally, the experimental results show that the KPDR method not only satisfies the diversity of l 3 / 4 , but also increases the anonymous space, reduces the communication overhead, ensures the anonymous success rate of users, and effectively prevents the disclosure of user privacy.

Bio-Inspired Private Information Retrieval System over Cloud Service Using the Social Bees' Lifestyle with a 3D Visualisation

2015 ◽  
pp. 201-228 ◽  
Author(s):  
Hadj Ahmed Bouarara ◽  
Reda Mohamed Hamou ◽  
Amine Abdelmalek
Keyword(s):  
Cloud Computing ◽  
Information Retrieval ◽  
Private Information ◽  
3D Visualization ◽  
Cloud Service ◽  
Private Information Retrieval ◽  
Digital Information ◽  
New Paradigm ◽  
User Privacy ◽  
Social Bees

In the last decade, a new paradigm had seen the light named Cloud Computing, which allows the delocalization of data and applications on a dematerialized infrastructure accessible from Internet. Unfortunately, the cloud services are facing many drawbacks especially in terms of security and data confidentiality. However, in a world where digital information is everywhere, finding the desired information has become a crucial problem. For the purpose to preserve the user privacy life new approaches and ideas had been published. The content of this chapter is a new system of bio-inspired private information retrieval (BI-PIR) using the lifestyle of social bees, which allows both to find and hid, the sensitive desired information. It is based on a multi-filters cryptosystem used by the server for the encryption of stored document and the retrieval model using a combination of filters by 3 types of workers bees (Purveyor, guardian and cleaner), the queen bee represents the query, and the hive represents the class of relevant documents. We have tested this system on the benchmark MEDLINE dataset with panoply of validation tools (recall, precision, f-measure, entropy, silence, noise, and accuracy) and a comparative study had been realized with other systems existed in literature. Finally, a 3D visualization tool had been developed in order to make the results in graphical format understandable by humans. Our objectives is to improve the services quality of cloud computing.

Fault-tolerant symmetrically-private information retrieval

2016 ◽  
Vol 30 (25) ◽  
pp. 1650178
Author(s):  
Tian-Yin Wang ◽  
Xiao-Qiu Cai ◽  
Rui-Ling Zhang
Keyword(s):  
Information Retrieval ◽  
Private Information ◽  
Quantum Key Distribution ◽  
Fault Tolerant ◽  
The Other ◽  
Private Information Retrieval ◽  
Large Database ◽  
User Privacy ◽  
Collective Rotation ◽  
Collective Rotation Noise

We propose two symmetrically-private information retrieval protocols based on quantum key distribution, which provide a good degree of database and user privacy while being flexible, loss-resistant and easily generalized to a large database similar to the precedent works. Furthermore, one protocol is robust to a collective-dephasing noise, and the other is robust to a collective-rotation noise.

scholarly journals A Fair and Privacy-Preserving Image Trading System Based on Blockchain and Group Signature

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Le Wang ◽  
Xuefeng Liu ◽  
Xiaodong Lin
Keyword(s):  
Private Information ◽  
Service Providers ◽  
Privacy Preserving ◽  
Group Signature ◽  
Communication Overhead ◽  
Source Image ◽  
User Privacy ◽  
Trading System ◽  
Daily Lives ◽  
Smart Contract

With the rise of digital images in our daily lives, there is a growing need to provide an image trading market where people can monetize their images and get desired images at prices that fit their budget. Those images are usually uploaded and stored onto centralized image trading service providers’ servers and the transactions for image trading are processed by these providers. Unfortunately, transaction unfairness and users’ privacy breaches have become major concerns since the service providers might be untrusted and able to manipulate image trading prices and infer users’ private information. Recently, several approaches have been proposed to address the unfairness issue by using the decentralized ledger technique and smart contract, but users’ privacy protection is not considered. In this paper, we propose a fair and privacy-preserving protocol that supports image fair exchange and protect user privacy. In particular, we exploit blockchain and Merkle tree to construct a fair image trading protocol with low communication overhead based on smart contract, which serves as an external judge that resolves disputes between buyers and sellers in image transactions. Moreover, we extend a popular short group signature scheme to protect users’ identity privacy, prevent linkability of transactions from being inferred, and ensure traceability of malicious users who may sell fake images and/or refuse to pay. Finally, we design and build a practical and open-source image trading system to evaluate the performance of our proposed protocol. Experimental results demonstrate its effectiveness and efficiency in real-world applications.

Bio-Inspired Private Information Retrieval System Over Cloud Service Using the Social Bees' Lifestyle With a 3D Visualisation

2018 ◽  
pp. 1471-1496
Author(s):  
Hadj Ahmed Bouarara ◽  
Reda Mohamed Hamou ◽  
Amine Abdelmalek
Keyword(s):  
Cloud Computing ◽  
Information Retrieval ◽  
Private Information ◽  
3D Visualization ◽  
Cloud Service ◽  
Private Information Retrieval ◽  
Digital Information ◽  
New Paradigm ◽  
User Privacy ◽  
Social Bees

In the last decade, a new paradigm had seen the light named Cloud Computing, which allows the delocalization of data and applications on a dematerialized infrastructure accessible from Internet. Unfortunately, the cloud services are facing many drawbacks especially in terms of security and data confidentiality. However, in a world where digital information is everywhere, finding the desired information has become a crucial problem. For the purpose to preserve the user privacy life new approaches and ideas had been published. The content of this chapter is a new system of bio-inspired private information retrieval (BI-PIR) using the lifestyle of social bees, which allows both to find and hid, the sensitive desired information. It is based on a multi-filters cryptosystem used by the server for the encryption of stored document and the retrieval model using a combination of filters by 3 types of workers bees (Purveyor, guardian and cleaner), the queen bee represents the query, and the hive represents the class of relevant documents. We have tested this system on the benchmark MEDLINE dataset with panoply of validation tools (recall, precision, f-measure, entropy, silence, noise, and accuracy) and a comparative study had been realized with other systems existed in literature. Finally, a 3D visualization tool had been developed in order to make the results in graphical format understandable by humans. Our objectives is to improve the services quality of cloud computing.

scholarly journals Efficient Private Information Retrieval Protocol with Homomorphically Computing Univariate Polynomials

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Wenju Xu ◽  
Baocang Wang ◽  
Rongxing Lu ◽  
Quanbo Qu ◽  
Yange Chen ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Open Problem ◽  
Private Information ◽  
Homomorphic Encryption ◽  
Communication Overhead ◽  
Private Information Retrieval ◽  
Secret Key ◽  
Communication Efficiency ◽  
Database Size ◽  
Univariate Polynomials

Private information retrieval (PIR) protocol is a powerful cryptographic tool and has received considerable attention in recent years as it can not only help users to retrieve the needed data from database servers but also protect them from being known by the servers. Although many PIR protocols have been proposed, it remains an open problem to design an efficient PIR protocol whose communication overhead is irrelevant to the database size N . In this paper, to answer this open problem, we present a new communication-efficient PIR protocol based on our proposed single-ciphertext fully homomorphic encryption (FHE) scheme, which supports unlimited computations with single variable over a single ciphertext even without access to the secret key. Specifically, our proposed PIR protocol is characterized by combining our single-ciphertext FHE with Lagrange interpolating polynomial technique to achieve better communication efficiency. Security analyses show that the proposed PIR protocol can efficiently protect the privacy of the user and the data in the database. In addition, both theoretical analyses and experimental evaluations are conducted, and the results indicate that our proposed PIR protocol is also more efficient and practical than previously reported ones. To the best of our knowledge, our proposed protocol is the first PIR protocol achieving O 1 communication efficiency on the user side, irrelevant to the database size N .

scholarly journals Provably Secure Symmetric Private Information Retrieval with Quantum Cryptography

Entropy ◽  
2020 ◽  
Vol 23 (1) ◽  
pp. 54
Author(s):  
Wen Yu Kon ◽  
Charles Ci Wen Lim
Keyword(s):  
Information Retrieval ◽  
Private Information ◽  
Secure Communication ◽  
Practical Implementation ◽  
Private Information Retrieval ◽  
User Privacy ◽  
Secret Keys ◽  
Shared Secret ◽  
Classical Quantum ◽  
Provably Secure

Private information retrieval (PIR) is a database query protocol that provides user privacy in that the user can learn a particular entry of the database of his interest but his query would be hidden from the data centre. Symmetric private information retrieval (SPIR) takes PIR further by additionally offering database privacy, where the user cannot learn any additional entries of the database. Unconditionally secure SPIR solutions with multiple databases are known classically, but are unrealistic because they require long shared secret keys between the parties for secure communication and shared randomness in the protocol. Here, we propose using quantum key distribution (QKD) instead for a practical implementation, which can realise both the secure communication and shared randomness requirements. We prove that QKD maintains the security of the SPIR protocol and that it is also secure against any external eavesdropper. We also show how such a classical-quantum system could be implemented practically, using the example of a two-database SPIR protocol with keys generated by measurement device-independent QKD. Through key rate calculations, we show that such an implementation is feasible at the metropolitan level with current QKD technology.

The Protection of User Preference Privacy in Personalized Information Retrieval: Challenges and Overviews

Libri ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Zongda Wu ◽  
Chenglang Lu ◽  
Youlin Zhao ◽  
Jian Xie ◽  
Dongdong Zou ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Privacy Protection ◽  
User Preference ◽  
User Privacy ◽  
Server Side ◽  
Algorithm Efficiency ◽  
Important Study ◽  
Basic Reference ◽  
Complete Set ◽  
Technical Features

Abstract This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users’ privacy protection, i.e., it is required to comprehensively improve the security of users’ preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.

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