scholarly journals Enhanced Effective and Privacy Preserving Multi Keyword Search over Encrypted Data in Cloud Storage Using Blowfish Algorithm

2021 ◽  
Vol 12 (2) ◽  
pp. 2845-2853
Author(s):  
Ch. Chakradhara Rao, Et. al.
Keyword(s):  
Keyword Search ◽  
Data Retrieval ◽  
Specific Information ◽  
Authentication Code ◽  
Privacy And Security ◽  
Online Data ◽  
Comparison Results ◽  
Algorithm Comparison ◽  
Cloud Server ◽  
User Data

The data owner administers their data to the public cloud due to regulatory. Even this data encoded once it easily transmitted to the cloud. In order to ensure the privacy and security, cloud subscribers need a very different type of online data. This specific information must be germane to the recipient's query. The user to inspect the query too in the cloud with umpteen keywords can accomplish this. With the intention to defend the privacy of data, confidential data encoded before subcontracting by the metadata owner, attempting to make the traditional and efficient plaintext keyword search tactic pointless. Therefore, it is crucial to explore a secure data search service for encrypted user data. Due to the growing of massive number of digital users and legal documents in the cloud, umpteen keywords forced in the search request and documents returned in the order of their relevance to these keywords.Cloud assistance end-user demands cloud information by various paternoster inquiry, whichlabelled as umpteenkeywordstratified exploration over scrambled information. In the cloud server, all the client inquiries exchanged. Server looks through the significant matter by utilizing the harmonic equivalency and sends the applicable outcomes to the client. Information got from cloud server is in the scrambled configuration. To get to control to the client,Information proprietor furnishes with key for unscrambling of information. Message Authentication Code(MAC) calculation is utilized to check and confirm trustworthiness of information. Thusly this paper depicts the method of giving security to redistribute information on cloud and checking the trustworthiness of information using blowfish algorithm. Comparison results shows the improvement in efficiency of Data Retrieval and Time efficiency.

scholarly journals Efficient verifiable fuzzy keyword search over encrypted data in cloud computing

2013 ◽  
Vol 10 (2) ◽  
pp. 667-684 ◽  
Author(s):  
Jianfeng Wang ◽  
Hua Ma ◽  
Qiang Tang ◽  
Jin Li ◽  
Hui Zhu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Keyword Search ◽  
Efficiency Analysis ◽  
Sensitive Data ◽  
Encrypted Data ◽  
Proposed Model ◽  
Cloud Server ◽  
Encryption Schemes ◽  
User Data ◽  
Fuzzy Keyword Search

As cloud computing becomes prevalent, more and more sensitive data is being centralized into the cloud by users. To maintain the confidentiality of sensitive user data against untrusted servers, the data should be encrypted before they are uploaded. However, this raises a new challenge for performing search over the encrypted data efficiently. Although the existing searchable encryption schemes allow a user to search the encrypted data with confidentiality, these solutions cannot support the verifiability of searching result. We argue that a cloud server may be selfish in order to save its computation ability or bandwidth. For example, it may execute only a fraction of the search and returns part of the searching result. In this paper, we propose a new verifiable fuzzy keyword search scheme based on the symbol-tree which not only supports the fuzzy keyword search, but also enjoys the verifiability of the searching result. Through rigorous security and efficiency analysis, we show that our proposed scheme is secure under the proposed model, while correctly and efficiently realizing the verifiable fuzzy keyword search. The extensive experimental results demonstrate the efficiency of the proposed scheme.

scholarly journals Implementation of User Centric SSE for Privacy-Preserving and Enhancing Searching Efficiency in Cloud Environment

2019 ◽  
Vol 8 (10) ◽  
pp. 3093-3098
Keyword(s):  
Cloud Computing ◽  
Keyword Search ◽  
Financial Model ◽  
Encrypted Data ◽  
Searchable Symmetric Encryption ◽  
Cloud Server ◽  
User Data ◽  
And Storage ◽  
Cloud Users ◽  
Access Data

Cloud computing allows the users geographically located to access data and application from a cloud which follows the pay-as-you-go financial model. This technology provides a method to enhance the capabilities dynamically without having to spend in new infrastructure or training personnel. Cloud computing promises to offer reliable services to the customer through the construction of next-generation data centers and storage technology. With its wide advantages, cloud computing has emerged as fast emergent segments of the IT. Hence data security is a major concern for cloud users. One solution to this is that user can apply encryption techniques on data before sending it to the cloud server. But encrypted data limits the server’s capability to make plaintext keyword search. Keyword search functionality that can function over the encrypted data is desirable but no information about the searched keyword or the retrieved document should not compromise in this process. Our implementation of searchable symmetric encryption proves that it is not vulnerable to such things and preserves privacy of user data and query.

Sistem Keamanan Gedung Menggunakan Kinect Xbox 360 Dengan Metode Skeletal Tracking

2021 ◽  
Vol 5 (6) ◽  
pp. 1137-1142
Author(s):  
Hamdi Alchudri ◽  
Zaini
Keyword(s):  
Optical Data ◽  
Visual Images ◽  
The Internet ◽  
Transmission Method ◽  
Sensor Reading ◽  
Loss Of Life ◽  
Analog To Digital ◽  
Cloud Server ◽  
User Data ◽  
The Internet Of Things

The incidence of fire and theft is very threatening and causes disruption to people's lifestyles, both due to natural and human factors resulting in loss of life, damage to the environment, loss of property and property, and psychological impacts. The purpose of this study is to create a building security system using Kinect Xbox 360 which can be used to detect fires and loss of valuable objects. The data transmission method uses the Internet of Things (IoT) and skeletal tracking. Skeletal detection uses Arduino Uno which is connected to a fire sensor and Kinect to detect suspicious movements connected to a PC. Kinect uses biometric authentication to automatically enter user data by recognizing objects and detecting skeletons including height, facial features and shoulder length. The ADC (Analog to Digital Converter) value of the fire sensor reading has a range between 200-300. The fire sensor detects the presence of fire through optical data analysis containing ultraviolet, infrared or visual images of fire. The data generated by Kinect by detecting the recognition of the skeleton of the main point of the human body known as the skeleton, where the reading point is authenticated by Kinect from a range of 1.5-3 meters which is declared the optimal measurement, and if a fire occurs, the pump motor will spray water randomly. to extinguish the fire that is connected to the internet via the wifi module. The data displayed is in the form of a graph on the Thingspeak cloud server service. Notification of fire and theft information using the delivery system from input to database

scholarly journals A Systematic Review of Research Studies Examining Telehealth Privacy and Security Practices Used By Healthcare Providers

2017 ◽  
Vol 9 (2) ◽  
pp. 39-58 ◽  
Author(s):  
Valerie J.M. Watzlaf ◽  
Leming Zhou ◽  
Dilhari R. DeAlmeida ◽  
Linda M. Hartman
Keyword(s):  
Systematic Review ◽  
Computer Security ◽  
Healthcare Providers ◽  
The United States ◽  
Specific Information ◽  
Exclusion Criteria ◽  
Privacy And Security ◽  
Security Practices ◽  
Meta Analyses ◽  
Encryption And Authentication

The objective of this systematic review was to systematically review papers in the United States that examine current practices in privacy and security when telehealth technologies are used by healthcare providers. A literature search was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). PubMed, CINAHL and INSPEC from 2003 – 2016 were searched and returned 25,404 papers (after duplications were removed). Inclusion and exclusion criteria were strictly followed to examine title, abstract, and full text for 21 published papers which reported on privacy and security practices used by healthcare providers using telehealth.  Data on confidentiality, integrity, privacy, informed consent, access control, availability, retention, encryption, and authentication were all searched and retrieved from the papers examined. Papers were selected by two independent reviewers, first per inclusion/exclusion criteria and, where there was disagreement, a third reviewer was consulted. The percentage of agreement and Cohen’s kappa was 99.04% and 0.7331 respectively. The papers reviewed ranged from 2004 to 2016 and included several types of telehealth specialties. Sixty-seven percent were policy type studies, and 14 percent were survey/interview studies. There were no randomized controlled trials. Based upon the results, we conclude that it is necessary to have more studies with specific information about the use of privacy and security practices when using telehealth technologies as well as studies that examine patient and provider preferences on how data is kept private and secure during and after telehealth sessions.Keywords: Computer security, Health personnel, Privacy, Systematic review, Telehealth 

Secure Data Validation and Transmission In Cloud and IoT Through Ban Logic And KP-ABE

2021 ◽  
Vol 11 ◽  
Author(s):  
Narander Kumar ◽  
Jitendra Kumar Samriya
Keyword(s):  
Privacy Preservation ◽  
Data Science ◽  
User Authentication ◽  
Ban Logic ◽  
Data Validation ◽  
Security Measures ◽  
Privacy And Security ◽  
Cloud Data ◽  
Control Approach ◽  
User Data

Background: Cloud computing is a service that is being accelerating its growth in the field of information technology in recent years. Privacy and security are challenging issues for cloud users and providers. Obective: This work aims at ensuring secured validation of user and protects data during transmission for users in a public IoT-cloud environment. Existing security measures however fails by their single level of security, adaptability for large amount of data and reliability. Therefore, to overcome these issues and to achieve a better solution for vulnerable data. Method: The suggested method utilizes a secure transmission in cloud using key policy attribute based encryption (KPABE). Initially, user authentication is verified. Then the user data is encrypted with the help of KP-ABE algorithm. Finally, data validation and privacy preservation are done by Burrows-Abadi-Needham (BAN) logic. This verified, and shows that the proposed encryption is correct, secure and efficient to prevent unauthorized access and prevention of data leakage so that less chances of data/identity, theft of a user is the analysis and performed by KP-ABE, that is access control approach. Results: Here the method attains the maximum of 88.35% of validation accuracy with a minimum 8.78ms encryption time, which is better when, compared to the existing methods. The proposed mechanism is done by MATLAB. The performance of the implemented method is calculated based on the time of encryption and decryption, execution time and validation accuracy. Conclusion: Thus the proposed approach attains the high IoT-cloud data security and increases the speed for validation and transmission with high accuracy and used for cyber data science processing.

scholarly journals A Multi-User Public Key Encryption with Multi-Keyword Search out of Bilinear Pairings

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6962
Author(s):  
Shuo Zhang ◽  
Qiaoyan Wen ◽  
Wenmin Li ◽  
Hua Zhang ◽  
Zhengping Jin
Keyword(s):  
Keyword Search ◽  
Daily Life ◽  
Bilinear Pairings ◽  
User Model ◽  
Public Key ◽  
Public Key Encryption ◽  
Private Cloud ◽  
Important Data ◽  
Cloud Server ◽  
Iot Devices

Internet of Things (IoT) and cloud computing are adopted widely in daily life and industrial production. Sensors of IoT equipment gather personal, sensitive and important data, which is stored in a cloud server. The cloud helps users to save cost and collaborate. However, the privacy of data is also at risk. Public-key encryption with keyword search (PEKS) is convenient for users to use the data without leaking privacy. In this article, we give a scheme of PEKS for a multi-user to realize the multi-keyword search at once and extend it to show a rank based on keywords match. The receiver can finish the search by himself or herself. With private cloud and server cloud, most users’ computing can be outsourced. Moreover, the PEKS can be transferred to a multi-user model in which the private cloud is used to manage receivers and outsource. The store cloud and the private cloud both obtain nothing with the keyword information. Then our IoT devices can easily run these protocols. As we do not use any pairing operations, the scheme is under more general assumptions that means the devices do not need to take on the heavy task of calculating pairing.

Optimal Elliptic Curve Cryptography-Based Effective Approach for Secure Data Storage in Clouds

2020 ◽  
Vol 11 (4) ◽  
pp. 65-81
Author(s):  
Anju Malik ◽  
Mayank Aggarwal ◽  
Bharti Sharma ◽  
Akansha Singh ◽  
Krishna Kant Singh
Keyword(s):  
Elliptic Curve ◽  
Data Storage ◽  
Elliptic Curve Cryptography ◽  
Search Algorithm ◽  
Distributed Storage ◽  
Data Retrieval ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensitive Data ◽  
Cloud Server

With the rapid development of cloud advancement, a data security challenge has emerged. In this paper, a technique based on elliptical cryptography and cuckoo search algorithm is proposed. With this technique, data owners securely store their data files in the cloud server. Initially the user sends a file storage request to store a file in a cloud server provider (CSP). The input file is checked whether it is sensitive or non-sensitive by the user. If the file is sensitive, then it would be split and stored in different virtual machines (VMs), and if the file is non-sensitive, then it would be assigned in a single VM. This approach was used for the first time as per the survey. To add further security, the sensitive data retrieval needs an encryption process that is supported by the proposed algorithm. If the data owner stores the sensitive data to cloud server, the data owner's document is encrypted by the double encryption technique. Here RSA and optimal elliptic curve cryptography (OECC) algorithm is used to encrypt the document with high security. The authors have used cuckoo search algorithm to identify the optimal key in ECC. This paper has proposed a novel cryptography approach for delivering mass distributed storage by which user's original data cannot be directly reached by cloud operators. Hence, this research has proved that the proposed work will give better securable data storage solving the security issues.

Privacy-Preserving Outsourced Similarity Search

2014 ◽  
Vol 25 (3) ◽  
pp. 48-71 ◽  
Author(s):  
Stepan Kozak ◽  
David Novak ◽  
Pavel Zezula
Keyword(s):  
Similarity Search ◽  
Data Privacy ◽  
System Analysis ◽  
Keyword Search ◽  
Evaluation Criteria ◽  
Similarity Index ◽  
Data Retrieval ◽  
Privacy Preserving ◽  
Scientific Data ◽  
Sensitive Data

The general trend in data management is to outsource data to 3rd party systems that would provide data retrieval as a service. This approach naturally brings privacy concerns about the (potentially sensitive) data. Recently, quite extensive research has been done on privacy-preserving outsourcing of traditional exact-match and keyword search. However, not much attention has been paid to outsourcing of similarity search, which is essential in content-based retrieval in current multimedia, sensor or scientific data. In this paper, the authors propose a scheme of outsourcing similarity search. They define evaluation criteria for these systems with an emphasis on usability, privacy and efficiency in real applications. These criteria can be used as a general guideline for a practical system analysis and we use them to survey and mutually compare existing approaches. As the main result, the authors propose a novel dynamic similarity index EM-Index that works for an arbitrary metric space and ensures data privacy and thus is suitable for search systems outsourced for example in a cloud environment. In comparison with other approaches, the index is fully dynamic (update operations are efficient) and its aim is to transfer as much load from clients to the server as possible.

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