scholarly journals Security Analysis and Preserving Block-Level Data DE-duplication in Cloud Storage Services

2020 ◽  
Vol 2 (2) ◽  
pp. 120-126 ◽  
Author(s):  
Adithya M. ◽  
Dr. Shanthini B.
Keyword(s):  
Distributed Storage ◽  
Security Analysis ◽  
Space Design ◽  
Secure Information ◽  
Information Accessibility ◽  
Level Data ◽  
Block Level ◽  
Potential Applications ◽  
Cloud Storage Services ◽  
Current Plan

Secure information deduplication can altogether decrease the correspondence and capacity overheads in distributed storage benefits and has potential applications in our large information-driven society. Existing information deduplication plans are commonly intended to either oppose savage power assaults or guarantee the effectiveness and information accessibility, yet not the two conditions. We are additionally not mindful of any current plan that accomplishes responsibility, in the feeling of lessening copy data divulgence (e.g., to decide if plain-writings of two scrambled messages are indistinguishable). Right now, examine the three-level cross-space design and propose an effective and protection safeguarding huge information deduplication in distributed storage (from now on alluded to as EPCDD). EPCDD accomplishes both protection safeguarding and information accessibility and opposes beast power assaults. Plus, we consider the responsibility to offer preferable protection affirmations over existing plans. We at that point show that EPCDD beats existing contending plans, as far as calculation, correspondence, and capacity overheads. Additionally, the time unpredictability of copy search in EPCDD is logarithmic.

scholarly journals Deduplication in Cloud Storage

2019 ◽  
Vol 9 (2S) ◽  
pp. 364-368
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Cloud Service ◽  
Information Storage ◽  
Cloud Environment ◽  
Data Deduplication ◽  
Cloud Service Provider ◽  
Level Data ◽  
Block Level ◽  
Individual Client

Cloud Computing is well known today on account of enormous measure of data storage and quick access of information over the system. It gives an individual client boundless extra space, accessibility and openness of information whenever at anyplace. Cloud service provider can boost information storage by incorporating data deduplication into cloud storage, despite the fact that information deduplication removes excess information and reproduced information happens in cloud environment. This paper presents a literature survey alongside different deduplication procedures that have been based on cloud information storage. To all the more likely guarantee secure deduplication in cloud, this paper examines file level data deduplication and block level data deduplication.

scholarly journals Security Analysis and Improvements on a Remote Integrity Checking Scheme for Regenerating-Coding-Based Distributed Storage

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Guangjun Liu ◽  
Wangmei Guo ◽  
Ximeng Liu ◽  
Jinbo Xiong
Keyword(s):  
Distributed Storage ◽  
Security Analysis ◽  
Data Integrity ◽  
Integrity Checking ◽  
Cloud Server ◽  
Data Integrity Checking ◽  
Checking Scheme ◽  
Data Auditing ◽  
Distributed Cloud ◽  
Remote Data

Enabling remote data integrity checking with failure recovery becomes exceedingly critical in distributed cloud systems. With the properties of a lower repair bandwidth while preserving fault tolerance, regenerating coding and network coding (NC) have received much attention in the coding-based storage field. Recently, an outstanding outsourced auditing scheme named NC-Audit was proposed for regenerating-coding-based distributed storage. The scheme claimed that it can effectively achieve lightweight privacy-preserving data verification remotely for these networked distributed systems. However, our algebraic analysis shows that NC-Audit can be easily broken due to a potential defect existing in its schematic design. That is, an adversarial cloud server can forge some illegal blocks to cheat the auditor with a high probability when the coding field is large. From the perspective of algebraic security, we propose a remote data integrity checking scheme RNC-Audit by resorting to hiding partial critical information to the server without compromising system performance. Our evaluation shows that the proposed scheme has significantly lower overhead compared to the state-of-the-art schemes for distributed remote data auditing.

scholarly journals Data Deduplication Strategies in Cloud Computing

2020 ◽  
Vol 5 (8) ◽  
pp. 734-738
Author(s):  
MD. Jareena Begum ◽  
B. Haritha
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Distributed Storage ◽  
The Internet ◽  
Data Deduplication ◽  
Secure Information ◽  
Pervasive Access

Cloud computing assumes an essential job in the business stage as figuring assets are conveyed on request to clients over the Internet. Distributed computing gives on-request and pervasive access to a concentrated pool of configurable assets, for example, systems, applications, and administrations This guarantees the vast majority of undertakings and number of clients externalize their information into the cloud worker. As of late, secure deduplication strategies have bid extensive interests in the both scholastic and mechanical associations. The primary preferred position of utilizing distributed storage from the clients' perspective is that they can diminish their consumption in buying and keeping up capacity framework. By the creating data size of appropriated registering, a decline in data volumes could help providers reducing the costs of running gigantic accumulating system and saving power usage. So information deduplication strategies have been proposed to improve capacity effectiveness in cloud stockpiles. Also, thinking about the assurance of delicate documents. Before putting away the records into the cloude stockpile they frequently utilize some encryption calculations to ensure them.In this paper we propose stratagies for secure information deduplication

scholarly journals Geography of racial coresidence

2021 ◽  
Author(s):  
Anna Dmowska ◽  
Tomasz Stepinski
Keyword(s):  
Metropolitan Areas ◽  
Data Driven ◽  
Racial Groups ◽  
Census Block ◽  
Asian Populations ◽  
Racial Preferences ◽  
Level Data ◽  
Geographical Regions ◽  
Block Level ◽  
Us Cities

Whereas most work on residential race relations in US cities is based on the concept of segregation, our approach studies this issue from a who-lives-with-whom perspective. To this end, we study coresidence profiles – percentages of a given racial subpopulation living in different population zones. Population zones are data-driven divisions of a city based on characteristic racial compositions. We used 1990 and 2010 decennial census block-level data for 61 largest US metropolitan areas to calculate coresidence profiles for four major racial subpopulations in each city at both years. Profiles for each race/year combination were clustered into three archetypes. Cities, where given race profiles belong to the same archetype, have similar coresidence patterns with respect to this race. We present the geographic distributions of co-habitation profiles and show how they changed during the 1990-2010 period. Our results revealed that coresidence profiles depend not only on racial preferences but also on the availability of racial groups; cities in the different geographical regions have different coresidence profiles because they have different shares of White, Black, Hispanic, and Asian subpopulations. Temporal changes in coresidence profiles are linked to the increased share of Hispanic and Asian populations.

scholarly journals County-level recruitment in online samples: Applications to COVID-19 and beyond

2020 ◽  
Author(s):  
Leib Litman ◽  
Robert Hartman ◽  
Shalom Noach Jaffe ◽  
Jonathan Robinson
Keyword(s):  
Infection Rate ◽  
Face Mask ◽  
The Self ◽  
Data Sets ◽  
County Level ◽  
Sampling Methodology ◽  
Individual Level ◽  
Level Data ◽  
Potential Applications ◽  
Present Effort

Thousands of readily downloadable county-level data sets offer untapped potential for linking geo-social influences to individual-level human behavior. In this study we describe a methodology for county-level sampling of online participants, allowing us to link the self-reported behavior of N = 1084 online respondents to contemporaneous county-level data on COVID-19 infection rate density. Using this approach, we show that infection rate density predicts person-level self-reported face mask wearing beyond multiple other demographic and attitudinal covariates. Using the present effort as a demonstration project, we describe the underlying sampling methodology and discuss the wider range of potential applications.

A Novel Approach for Encrypted Data-Deduplication in Clouds

2020 ◽  
Vol 17 (8) ◽  
pp. 3631-3635
Author(s):  
L. Mary Gladence ◽  
Priyanka Reddy ◽  
Apoorva Shetty ◽  
E. Brumancia ◽  
Senduru Srinivasulu
Keyword(s):  
Data Transfer ◽  
Distributed Storage ◽  
Security Analysis ◽  
Test Plot ◽  
Security Model ◽  
Proof Of Concept ◽  
Data Deduplication ◽  
Encrypted Data ◽  
Novel Approach ◽  
Encryption Method

Data deduplication is one of the main techniques for copying recovery data duplicates and was widely used in distributed storage to minimize extra space and spare data transfer capacity. It was proposed that the simultaneous encryption method encode the data before re-appropriating to preserve the confidentiality of delicate data while facilitating de replication. Unlike conventional de duplication systems, consumers are therefore viewed as having differential advantages as indupli-cate tests other than the data itself. Security analysis shows that our approach is safe in terms of the values set out in the proposed security model. For this deduplication M3 encryption algorithm and DES algorithm are used. M3 encryption is to compare another with the latest technology, for more effective, security purposes, fast actions and. The second DES encryption that was used to open the file and decrypt understandable language for humans in a secure language. A model of our current accepted copy check program is revised as proof of concept by the current research and explicitly shows the tests using our model. The proposed research shows that when opposed to conventional operations, our proposed duplicate test plot creates marginal overhead.

scholarly journals Secure Deduplication Based on Rabin Fingerprinting over Wireless Sensing Data in Cloud Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Yinghui Zhang ◽  
Haonan Su ◽  
Menglei Yang ◽  
Dong Zheng ◽  
Fang Ren ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Security Analysis ◽  
Operation Time ◽  
Communication Cost ◽  
Wireless Sensing ◽  
Data Deduplication ◽  
Sensing Data ◽  
Storage Overhead ◽  
Block Level ◽  
Cloud Users

The rapid advancements in the Internet of Things (IoT) and cloud computing technologies have significantly promoted the collection and sharing of various data. In order to reduce the communication cost and the storage overhead, it is necessary to exploit data deduplication mechanisms. However, existing data deduplication technologies still suffer security and efficiency drawbacks. In this paper, we propose two secure data deduplication schemes based on Rabin fingerprinting over wireless sensing data in cloud computing. The first scheme is based on deterministic tags and the other one adopts random tags. The proposed schemes realize data deduplication before the data is outsourced to the cloud storage server, and hence both the communication cost and the computation cost are reduced. In particular, variable-size block-level deduplication is enabled based on the technique of Rabin fingerprinting which generates data blocks based on the content of the data. Before outsourcing data to the cloud, users encrypt the data based on convergent encryption technologies, which protects the data from being accessed by unauthorized users. Our security analysis shows that the proposed schemes are secure against offline brute-force dictionary attacks. In addition, the random tag makes the second scheme more reliable. Extensive experimental results indicate that the proposed data deduplication schemes are efficient in terms of the deduplication rate, the system operation time, and the tag generation time.

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