Verifiable inner product computation on outsourced database for authenticated multi-user data sharing

2020 ◽  
Vol 539 ◽  
pp. 295-311
Author(s):  
Haining Yang ◽  
Ye Su ◽  
Jing Qin ◽  
Huaxiong Wang ◽  
Yongcheng Song
2019 ◽  
Vol 13 (4) ◽  
pp. 356-363
Author(s):  
Yuezhong Wu ◽  
Wei Chen ◽  
Shuhong Chen ◽  
Guojun Wang ◽  
Changyun Li

Background: Cloud storage is generally used to provide on-demand services with sufficient scalability in an efficient network environment, and various encryption algorithms are typically applied to protect the data in the cloud. However, it is non-trivial to obtain the original data after encryption and efficient methods are needed to access the original data. Methods: In this paper, we propose a new user-controlled and efficient encrypted data sharing model in cloud storage. It preprocesses user data to ensure the confidentiality and integrity based on triple encryption scheme of CP-ABE ciphertext access control mechanism and integrity verification. Moreover, it adopts secondary screening program to achieve efficient ciphertext retrieval by using distributed Lucene technology and fine-grained decision tree. In this way, when a trustworthy third party is introduced, the security and reliability of data sharing can be guaranteed. To provide data security and efficient retrieval, we also combine active user with active system. Results: Experimental results show that the proposed model can ensure data security in cloud storage services platform as well as enhance the operational performance of data sharing. Conclusion: The proposed security sharing mechanism works well in an actual cloud storage environment.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yunru Zhang ◽  
Debiao He ◽  
Kim-Kwang Raymond Choo

Internet of Things (IoT) and cloud computing are increasingly integrated, in the sense that data collected from IoT devices (generally with limited computational and storage resources) are being sent to the cloud for processing, etc., in order to inform decision making and facilitate other operational and business activities. However, the cloud may not be a fully trusted entity, like leaking user data or compromising user privacy. Thus, we propose a privacy-preserving and user-controlled data sharing architecture with fine-grained access control, based on the blockchain model and attribute-based cryptosystem. Also, the consensus algorithm in our system is the Byzantine fault tolerance mechanism, rather than Proof of Work.


2019 ◽  
Vol 62 (12) ◽  
pp. 1748-1760 ◽  
Author(s):  
Yang Chen ◽  
Wenmin Li ◽  
Fei Gao ◽  
Wei Yin ◽  
Kaitai Liang ◽  
...  

AbstractOnline data sharing has become a research hotspot while cloud computing is getting more and more popular. As a promising encryption technique to guarantee the security shared data and to realize flexible fine-grained access control, ciphertext-policy attribute-based encryption (CP-ABE) has drawn wide attentions. However, there is a drawback preventing CP-ABE from being applied to cloud applications. In CP-ABE, the access structure is included in the ciphertext, and it may disclose user’s privacy. In this paper, we find a more efficient method to connect ABE with inner product encryption and adopt several techniques to ensure the expressiveness of access structure, the efficiency and security of our scheme. We are the first to present a secure, efficient fine-grained access control scheme with hidden access structure, the access structure can be expressed as AND-gates on multi-valued attributes with wildcard. We conceal the entire attribute instead of only its values in the access structure. Besides, our scheme has obvious advantages in efficiency compared with related schemes. Our scheme can make data sharing secure and efficient, which can be verified from the analysis of security and performance.


2014 ◽  
Vol 686 ◽  
pp. 220-225
Author(s):  
Guo Sheng Ma ◽  
Xiao Bo Xia

Remote data monitoring system which adopts virtual instrument usually applies data sharing, acquisition and remote transmission technology via internet. It is able to finish concurrent data acquisition and processing for multi-user and multi-task and also build a personalized virtual testing environment for more people but with fewer instruments. In this paper, we’ll elaborate on the design and implementation of information sharing platform through a typical example of how to build multi-user concurrent virtual testing environment based on the virtual software LabVIEW.


2020 ◽  
Vol 33 (7) ◽  
pp. e4307 ◽  
Author(s):  
Chandrashekhar Meshram ◽  
Cheng-Chi Lee ◽  
Abhay S. Ranadive ◽  
Chun-Ta Li ◽  
Sarita Gajbhiye Meshram ◽  
...  

Author(s):  
Tarasvi Lakum ◽  
Barige Thirumala Rao

<p><span>In this paper, we are proposing a mutual query data sharing protocol (MQDS) to overcome the encryption or decryption time limitations of exiting protocols like Boneh, rivest shamir adleman (RSA), Multi-bit transposed ring learning parity with noise (TRLPN), ring learning parity with noise (Ring-LPN) cryptosystem, key-Ordered decisional learning parity with noise (kO-DLPN), and KD_CS protocol’s. Titled scheme is to provide the security for the authenticated user data among the distributed physical users and devices. The proposed data sharing protocol is designed to resist the chosen-ciphertext attack (CCA) under the hardness solution for the query shared-strong diffie-hellman (SDH) problem. The evaluation of proposed work with the existing data sharing protocols in computational and communication overhead through their response time is evaluated.</span></p>


JAMIA Open ◽  
2021 ◽  
Author(s):  
Ram D Gopal ◽  
Hooman Hidaji ◽  
Raymond A Patterson ◽  
Niam Yaraghi

Abstract Objectives To examine the impact of COVID-19 pandemic on the extent of potential violations of Internet users’ privacy. Materials and Methods We conducted a longitudinal study of the data sharing practices of the top 1,000 websites in the US between April 9th and August 27th, 2020. We fitted a conditional latent growth curve model on the data to examine the longitudinal trajectory of the third-party data sharing over the 21 weeks period of the study and examine how website characteristics affect this trajectory. We denote websites that asked for permission before placing cookies on users’ browsers as "privacy-respecting". Results As the weekly number of COVID-19 deaths increased by 1,000, the average number of third parties increased by 0.26 [95%CI, 0.15 to 0.37] P&lt;.001 units in the next week. This effect was more pronounced for websites with higher traffic as they increased their third parties by an additional 0.41 [95% CI, 0.18 to 0.64]; P&lt;.001 units per week. However, privacy respecting websites that experienced a surge in traffic reduced their third parties by 1.01 [95% CI, -2.01 to 0]; P = 0.05 units per week in response to every 1,000 COVID-19 deaths in the preceding week. Discussion While in general websites shared their users’ data with more third parties as COVID-19 progressed in the US, websites’ expected traffic and respect for users’ privacy significantly affect such trajectory. Conclusions Attention should also be paid to the impact of the pandemic on elevating online privacy threats, and the variation in third-party tracking among different types of websites. Lay Summary As the COVID-19 pandemic progressed in the country, the demand for online services surged. As the level of Internet use increased, websites’ opportunity to track and monetize users’ data increased with it. In this research, we examine the extent to which websites increased the number of third-parties with which they share their user’ data and how such practices were moderated by a website’s level of respect for users’ privacy and traffic surge. We find that while the number of third parties increased over time, the websites with higher respect for privacy tend to decrease the number of their parties only if they also experience a significant increase in their traffic.


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