The document proposes the RASP (Random Space Perturbation) approach to build confidential and efficient range and k-nearest neighbor (kNN) query services in the cloud. RASP combines order preserving encryption, dimensionality expansion, random noise injection, and random projection to securely transform data while preserving ranges for efficient query processing. It defines the RASP perturbation method and constructs private range and kNN query services. Experimental results demonstrate advantages in efficiency and security.
Building confidential and efficient query services in the cloud with rasp dat...LeMeniz Infotech
Building confidential and efficient query services in the cloud with rasp data perturbation
With the wide deployment of public cloud computing infrastructures, using clouds to host data query services has become an appealing solution for the advantages on scalability and cost-saving. However, some data might be sensitive that the data owner does not want to move to the cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a secured query service should still provide efficient query processing and significantly reduce the in-house workload to fully realize the benefits of cloud computing. We propose the random space perturbation (RASP) data perturbation method to provide secure and efficient range query and kNN query services for protected data in the cloud. The RASP data perturbation method combines order preserving encryption, dimensionality expansion, random noise injection, and random projection, to provide strong resilience to attacks on the perturbed data and queries. Security.
Literature Survey on Buliding Confidential and Efficient Query Processing Usi...paperpublications3
Abstract: Hosting data query services with the deployed cloud computing infrastructure increase the scalability and high performance evaluations with low cost. However, some data owners might not be interested to the save their in the cloud environment because of data confidentiality and query processing privacy should be guaranteed by the cloud service providers. Secured Query should able to provide very high efficient of query processing and also should reduce in – house workload. In this paper we proposed RASP data perturbation techniques combines various objectives like random noise injection, dimensionality expansion, efficient encryption and random projection, henceforth RASP methodology are also used to preserves multidimensional ranges. KNN – R algorithm used to work with RASP range for processing KNN queries. The experimental result of our project carried out to define realistic security and threat model approaches for improved efficient and security.
Building confidential and efficient query services in the cloud with rasp dat...LeMeniz Infotech
Building confidential and efficient query services in the cloud with rasp data perturbation
With the wide deployment of public cloud computing infrastructures, using clouds to host data query services has become an appealing solution for the advantages on scalability and cost-saving. However, some data might be sensitive that the data owner does not want to move to the cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a secured query service should still provide efficient query processing and significantly reduce the in-house workload to fully realize the benefits of cloud computing. We propose the random space perturbation (RASP) data perturbation method to provide secure and efficient range query and kNN query services for protected data in the cloud. The RASP data perturbation method combines order preserving encryption, dimensionality expansion, random noise injection, and random projection, to provide strong resilience to attacks on the perturbed data and queries. Security.
Literature Survey on Buliding Confidential and Efficient Query Processing Usi...paperpublications3
Abstract: Hosting data query services with the deployed cloud computing infrastructure increase the scalability and high performance evaluations with low cost. However, some data owners might not be interested to the save their in the cloud environment because of data confidentiality and query processing privacy should be guaranteed by the cloud service providers. Secured Query should able to provide very high efficient of query processing and also should reduce in – house workload. In this paper we proposed RASP data perturbation techniques combines various objectives like random noise injection, dimensionality expansion, efficient encryption and random projection, henceforth RASP methodology are also used to preserves multidimensional ranges. KNN – R algorithm used to work with RASP range for processing KNN queries. The experimental result of our project carried out to define realistic security and threat model approaches for improved efficient and security.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Identifying the Performance Efficiency Of Attribute Based Encryption With Sec...IJSRD
Attribute-based encryption (ABE) can be used for the encryption of data with attributes and logs. Instead of encrypting each part of a log with the keys of all recipients, it is possible to encrypt the log only with attributes which match recipient’s attributes. This primitive can also be used for broadcast encryption in order to decrease the number of keys used. Here the access control will be given with the keys and the attributes. The outsourcing computation cost will be comparatively less when compared to the existing system. The data will be shared between the two users if and only if the key matches. In addition, for the first time, we propose an outsourced ABE construction which provides check ability of the outsourced computation results in an efficient way. The performance analysis has been proven this method to be more secured.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Optimizing Data Confidentiality using Integrated Multi Query ServicesIJTET Journal
Query services have experienced terribly massive growth within past few years for that reason large usage of services need to balance outsourcing data management to Cloud service providers that provide query services to the client for data owners, therefore data owner needs data confidentiality as well as query privacy to be guaranteed attributable to disloyal behavior of cloud service provider consequently enhancing data confidentiality must not be compromise the query processed performance. It is not significant to provide slow query services as the result of security along with privacy assurance. We propose the random space perturbation data perturbation method to provide secure with kNN(k-nearest-neighbor) range query services for protecting data in the cloud and Frequency Structured R-Tree (FSR-Tree) efficient range query. Our schemes enhance data confidentiality without compromising the FSR-TREE query processing performance that also increases the user experience.
Gagner Technologies offers M.E projects based on IEEE 2014 . M.Phil Research projects,Final Year Projects, M.E projects 2014-2015, mini projects 2014-2015, Real Time Projects, Final Year Projects for BE ECE, CSE, IT, MCA, B TECH, ME, M SC (IT), BCA, BSC CSE, IT IEEE 2013 Projects in Data Mining, Distributed System, Mobile Computing, Networks, Networking. IEEE2014-2015 projects. Final Year Projects at Chennai, IEEE Software Projects, Engineering Projects, MCA projects, BE projects, JAVA projects, J2EE projects, .NET projects, Students projects, Final Year Student Projects, IEEE Projects 2014-2015, Real Time Projects, Final Year Projects for BE ECE, CSE, IT, MCA, B TECH, ME, M SC (IT), BCA, BSC CSE, IT,software Engineering
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Cloud storage provides a convenient, massive, and scalable storage at low cost, but data privacy is a major concern that prevents users from storing files on the cloud trustingly.
Efficient Implementation of Proof of Retrievability (OPOR) In Cloud Computing...IJERA Editor
Cloud computing has become an integral part of IT services, storing the application softwares and databases in
large centralized shared data servers. Since it’s a shared platform, the data and services may not be fully trust
worthy. In this work, we have implemented an efficient security model that ensures the data integrity of stored
data in cloud servers. The computational load of data verification linearly grows with the complexity of the
security model and this poses a serious problem at the resource constrained user’s end. Therefore to tackle this
problem we have implemented a new cloud storage scheme which ensures proof of retrivebility (OPoR) at a
third party cloud audit server to pre-process data before uploading into cloud storage server.
JPJ1404 Building Confidential And Efficient Query Services In The Cloud Wit...chennaijp
We are good ieee java projects development center in chennai and pondicherry. We guided advanced java techonolgies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Identifying the Performance Efficiency Of Attribute Based Encryption With Sec...IJSRD
Attribute-based encryption (ABE) can be used for the encryption of data with attributes and logs. Instead of encrypting each part of a log with the keys of all recipients, it is possible to encrypt the log only with attributes which match recipient’s attributes. This primitive can also be used for broadcast encryption in order to decrease the number of keys used. Here the access control will be given with the keys and the attributes. The outsourcing computation cost will be comparatively less when compared to the existing system. The data will be shared between the two users if and only if the key matches. In addition, for the first time, we propose an outsourced ABE construction which provides check ability of the outsourced computation results in an efficient way. The performance analysis has been proven this method to be more secured.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Optimizing Data Confidentiality using Integrated Multi Query ServicesIJTET Journal
Query services have experienced terribly massive growth within past few years for that reason large usage of services need to balance outsourcing data management to Cloud service providers that provide query services to the client for data owners, therefore data owner needs data confidentiality as well as query privacy to be guaranteed attributable to disloyal behavior of cloud service provider consequently enhancing data confidentiality must not be compromise the query processed performance. It is not significant to provide slow query services as the result of security along with privacy assurance. We propose the random space perturbation data perturbation method to provide secure with kNN(k-nearest-neighbor) range query services for protecting data in the cloud and Frequency Structured R-Tree (FSR-Tree) efficient range query. Our schemes enhance data confidentiality without compromising the FSR-TREE query processing performance that also increases the user experience.
Gagner Technologies offers M.E projects based on IEEE 2014 . M.Phil Research projects,Final Year Projects, M.E projects 2014-2015, mini projects 2014-2015, Real Time Projects, Final Year Projects for BE ECE, CSE, IT, MCA, B TECH, ME, M SC (IT), BCA, BSC CSE, IT IEEE 2013 Projects in Data Mining, Distributed System, Mobile Computing, Networks, Networking. IEEE2014-2015 projects. Final Year Projects at Chennai, IEEE Software Projects, Engineering Projects, MCA projects, BE projects, JAVA projects, J2EE projects, .NET projects, Students projects, Final Year Student Projects, IEEE Projects 2014-2015, Real Time Projects, Final Year Projects for BE ECE, CSE, IT, MCA, B TECH, ME, M SC (IT), BCA, BSC CSE, IT,software Engineering
For more details contact below Address
No 1,South Dhandapani street(opposite to T.Nagar Bus Stand),T.Nagar,chennai-17
Cloud storage provides a convenient, massive, and scalable storage at low cost, but data privacy is a major concern that prevents users from storing files on the cloud trustingly.
Efficient Implementation of Proof of Retrievability (OPOR) In Cloud Computing...IJERA Editor
Cloud computing has become an integral part of IT services, storing the application softwares and databases in
large centralized shared data servers. Since it’s a shared platform, the data and services may not be fully trust
worthy. In this work, we have implemented an efficient security model that ensures the data integrity of stored
data in cloud servers. The computational load of data verification linearly grows with the complexity of the
security model and this poses a serious problem at the resource constrained user’s end. Therefore to tackle this
problem we have implemented a new cloud storage scheme which ensures proof of retrivebility (OPoR) at a
third party cloud audit server to pre-process data before uploading into cloud storage server.
JPJ1404 Building Confidential And Efficient Query Services In The Cloud Wit...chennaijp
We are good ieee java projects development center in chennai and pondicherry. We guided advanced java techonolgies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
Key aggregate cryptosystem for scalable data sharing in cloud storage using pairng based cryptography. We used JPBC tool to implement Key Aggregate cryptosystem.
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SECURE & EFFICIENT AUDIT SERVICE OUTSOURCING FOR DATA INTEGRITY IN CLOUDSGyan Prakash
Cloud-based outsourced storage relieves the client’s load for storage management and maintenance by providing a comparably low-cost, scalable, location-independent platform. Though, the information that clients no longer have physical control of data specifies that they are facing a potentially formidable risk for missing or corrupted data. To avoid the security risks, inspection services are serious to ensure the integrity and availability of outsourced data and to achieve digital forensics and reliability on cloud computing. Provable data possession (PDP), which is a cryptographic method for validating the reliability of data without retrieving it at an untrusted server, can be used to realize audit services. In this project, profiting from the interactive zero-knowledge proof system, the construction of an interactive PDP protocol to prevent the fraudulence of prover (soundness property) and the leakage of verified data (zero knowledge property).To prove that our construction holds these properties based on the computation Diffie–Hellman assumption and the rewindable black-box knowledge extractor. An efficient mechanism on probabilistic queries and periodic verification is proposed to reduce the audit costs per verification and implement abnormal detection timely. Also, we present an efficient method for choosing an optimal parameter value to reduce computational overheads of cloud audit services.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Survey on Privacy- Preserving Multi keyword Ranked Search over Encrypted Clou...Editor IJMTER
The advent of cloud computing, data owners are motivated to outsource their complex
data management systems from local sites to commercial public cloud for great flexibility and
economic savings. But for protecting data privacy, sensitive data has to be encrypted before
outsourcing.Considering the large number of data users and documents in cloud, it is crucial for
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effective data retrieval need. Related works on searchable encryption focus on single keyword
search or Boolean keyword search, and rarely differentiate the search results. We first propose a
basic MRSE scheme using secure inner product computation, and then significantly improve it to
meet different privacy requirements in two levels of threat models. The Incremental High Utility
Pattern Transaction Frequency Tree (IHUPTF-Tree) is designed according to the transaction
frequency (descending order) of items to obtain a compact tree.
By using high utility pattern the items can be arranged in an efficient manner. Tree structure
is used to sort the items. Thus the items are sorted and frequent pattern is obtained. The frequent
pattern items are retrieved from the database by using hybrid tree (H-Tree) structure. So the
execution time becomes faster. Finally, the frequent pattern item that satisfies the threshold value
is displayed.
A time efficient approach for detecting errors in big sensor data on cloudLeMeniz Infotech
A time efficient approach for detecting errors in big sensor data on cloud
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Efficient Instant-Fuzzy Search with Proximity Ranking
System finds answers to a query instantly while user types in keywords character-by-character.
Fuzzy search improves user search experiences by finding relevant answers with keywords similar to query keywords.
A main computational challenge in this paradigm is the high speed requirement
At the same time, we also need good ranking functions that consider the proximity of keywords to compute relevance scores
The previous systems were able to recommend results based on just previously typed characters kept in cache module.
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Relevance to user query along with users intentions could be mined easily.
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KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
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ACEP Magazine edition 4th launched on 05.06.2024Rahul
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Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
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Building confidential and efficient query services in the cloud with rasp data perturbation
1. Building Confidential and Efficient Query
Services in the Cloud with RASP Data
Perturbation
ABSTRACT
With the wide deployment of public cloud computing infrastructures, using clouds to host
data query services has become an appealing solution for the advantages on scalability and cost-
saving. However, some data might be sensitive that the data owner does not want to move to the
cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a
secured query service should still provide efficient query processing and significantly reduce the
in-house workload to fully realize the benefits of cloud computing. We propose the RASP data
perturbation method to provide secure and efficient range query and kNN query services for
protected data in the cloud. The RASP data perturbation method combines order preserving
encryption, dimensionality expansion, random noise injection, and random projection, to provide
strong resilience to attacks on the perturbed data and queries. It also preserves multidimensional
ranges, which allows existing indexing techniques to be applied to speedup range query
processing. The kNN-R algorithm is designed to work with the RASP range query algorithm to
process the kNN queries. We have carefully analyzed the attacks on data and queries under a
precisely defined threat model and realistic security assumptions. Extensive experiments have
been conducted to show the advantages of this approach on efficiency and security.
.
Existing System
With the wide deployment of public cloud computing infrastructures, using clouds to host
data query services has become an appealing solution for the advantages on scalability and cost-
We develops Computer Engineering Projects for BE/ME students. For any kind of support you may live
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2. saving. However, some data might be sensitive that the data owner does not want to move to the
cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a
secured query service should still provide efficient query processing and significantly reduce the
in-house workload to fully realize the benefits of cloud computing.
Disadvantages
1. Adversaries, such as curious service providers, can possibly make a copy of the database
or eavesdrop users’ queries, which will be difficult to detect and prevent in the cloud
infrastructures.
Proposed System
We propose the RAndom Space Perturbation (RASP) approach to constructing practical
range query and k-nearest-neighbor (kNN) query services in
the cloud. The proposed approach will address all the 2 four aspects of the CPEL criteria and aim
to achieve a good balance on them. The basic idea is to randomly
transform the multidimensional datasets with a combination of order preserving encryption,
dimensionality expansion, random noise injection, and random project, so that the utility for
processing range queries is preserved. The RASP perturbation is designed in such a way that the
queried ranges are securely transformed into polyhedra in the RASP-perturbed data space, which
can be efficiently processed with the support of indexing structures in the perturbed space. The
RASP kNN query service (kNN-R) uses the RASP range query service to process kNN queries.
The key components in the RASP framework include (1) the definition and properties of RASP
perturbation; (2) the construction of the privacy-preserving range query services; (3) the
construction of privacy-preserving kNN query services; and (4) an analysis of the attacks on the
RASP-protected data and queries.
We develops Computer Engineering Projects for BE/ME students. For any kind of support you may live
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3. Advantages:
1. The RASP perturbation is a unique combination of OPE, dimensionality expansion,
random noise injection, and random projection, which provides strong confidentiality
guarantee.
2. The proposed service constructions are able to minimize the in-house processing
workload because of the low perturbation cost and high precision query results. This is an
important feature enabling practical cloud-based solutions.
ARCHITECTURE :
IMPLEMENTATION
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4. Implementation is the stage of the project when the theoretical design is
turned out into a working system. Thus it can be considered to be the most
critical stage in achieving a successful new system and in giving the user,
confidence that the new system will work and be effective.
The implementation stage involves careful planning, investigation of the
existing system and it’s constraints on implementation, designing of methods to
achieve changeover and evaluation of changeover methods.
Main Modules:-
1. User Module :
In this module, Users are having authentication and security to access the detail which is
presented in the ontology system. Before accessing or searching the details user should have the
account in that otherwise they should register first.
2. Multidimensional Index Tree :
Most multidimensional indexing algorithms are derived from R-tree like algorithms ,
where the axis-aligned minimum bounding region (MBR) is the construction block for indexing
the multidimensional data. For 2D data, an MBR is a rectangle. For higher dimensions, the shape
of MBR is extended to hyper-cube. the MBRs in the R-tree for a 2D dataset, where each node is
bounded by a node MBR. The R-tree range query algorithm compares the MBR and the queried
range
to find the answers.
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5. 3. Performance of kNN-R Query Processing :
In this set of experiments, we investigate several aspects of kNN query processing. (1)
We will study the cost of (k, δ)-Range algorithm, which mainly contributes to the server-side
cost. (2) We will show the overall cost distribution over the cloud side and the proxy server. (3)
We will show the advantages of kNN-R over another popular approach: the Casper approach for
privacy-preserving kNN search.
4.Preserving Query Privacy :
Private information retrieval (PIR) tries to fully preserve the privacy of access pattern,
while the data may not be encrypted. PIR schemes are normally very costly. Focusing on the
efficiency side of PIR, Williams et al. use a pyramid hash index to implement efficient privacy
preserving data-block operations based
on the idea of Oblivious RAM. It is different from our setting of high throughput range query
processing. Hu et al. addresses the query privacy problem and requires the authorized query
users, the data owner, and the cloud to collaboratively process kNN queries. However, most
computing tasks are done in the user’s local system with heavy interactions with the cloud
server. The cloud server only aids query processing, which does not meet the principle of
moving computing to the cloud.
We develops Computer Engineering Projects for BE/ME students. For any kind of support you may live
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6. System Configuration:-
H/W System Configuration:-
Processor - Pentium –III
Speed - 1.1 Ghz
RAM - 256 MB(min)
Hard Disk - 20 GB
Floppy Drive - 1.44 MB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
S/W System Configuration:-
Operating System :Windows95/98/2000/XP
Application Server : Tomcat5.0/6.X
Front End : HTML, Java, Jsp
Scripts : JavaScript.
Server side Script : Java Server Pages.
We develops Computer Engineering Projects for BE/ME students. For any kind of support you may live
chat with us at www.ocularsystems.in or call us on 020 30858066 or
Mail Us: info@ocularsystems.in
Our Address: Swagat Corner Building, Near Narayani Dham Temple, Katraj, Pune-46 (Maharashtra)
7. Database : Mysql 5.0
Database Connectivity : JDBC.
Conclusion :
We propose the RASP perturbation approach to hosting query services in the cloud,
which satisfies the CPEL criteria: data Confidentiality, query Privacy, Efficient query
processing, and Low in-house workload. The requirement on low in-house workload is a critical
feature to fully realize the benefits of cloud 15 computing, and efficient query processing is a key
measure of the quality of query services.
RASP perturbation is a unique composition of OPE, dimensionality expansion, random noise
injection, and random projection, which provides unique security features. It aims to preserve the
topology of the queried range in the perturbed space, and allows to use indices for efficient range
query processing. With the topology-preserving features, we are able to develop efficient range
query services to achieve sublinear time complexity of processing queries. We then develop the
kNN query service based on the range query service. The security of both the perturbed data and
the protected queries is carefully analyzed under a precisely defined threat model. We also
conduct several sets of experiments to show the efficiency of query processing and the low cost
of in-house processing. We will continue our studies on two aspects: (1) further improve the
performance of query processing for both range queries and kNN queries; (2) formally analyze
the leaked query and access patterns and the possible effect on both data and query
confidentiality.
We develops Computer Engineering Projects for BE/ME students. For any kind of support you may live
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Mail Us: info@ocularsystems.in
Our Address: Swagat Corner Building, Near Narayani Dham Temple, Katraj, Pune-46 (Maharashtra)