To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
This document discusses privacy concerns when collaboratively publishing horizontally partitioned data from multiple data providers. It introduces the concept of an "m-adversary", which is a group of up to m colluding data providers. It also introduces the notion of "m-privacy", which guarantees anonymity against such m-adversaries. The paper then presents algorithms for efficiently checking m-privacy while maximizing data utility and handling different m-adversary attack scenarios. Experiments on real datasets show the approach achieves better utility and efficiency than existing methods while providing m-privacy guarantees.
A Rule based Slicing Approach to Achieve Data Publishing and Privacyijsrd.com
several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving micro data publishing. Recent work has shown that generalization loses considerable amount of information, especially for high dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi-identifying attributes and sensitive attributes. The existing system proposed slicing concept to overcome the tuple based partition this has been done to overcome the previous generalization and bucketization. In this paper, present a novel technique called rule based slicing, which partitions the data both horizontally and vertically. We show that slicing preserves better data utility than generalization and can be used for membership disclosure protection. Another important advantage of slicing is that it can handle high-dimensional data. We show how slicing can be used for attribute disclosure protection and develop an efficient algorithm for computing the sliced data that obey the l-diversity requirement. The workload experiments confirm that slicing preserves better utility than generalization and is more effective than bucketization in workloads involving the sensitive attribute. The experiments also demonstrate that slicing can be used to prevent membership disclosure
Advanced SQL covers selecting columns, aggregate functions like MIN() and MAX(), the CASE WHEN statement, JOINs, the WHERE clause, GROUP BY, declaring variables, and subqueries
- AtomicDB uses a vector space model to represent data as interconnected informational elements at the center of their relationship universes, allowing each data item to act as an entry point into the network.
- Associations in AtomicDB are bidirectional references between data items, with no separate connector or predicate items. The algorithm that determines associations is entirely fact-based.
- Large datasets can be distributed across multiple servers by mapping data element tokens to different physical locations on contingent high-bandwidth networks.
The document discusses incentive compatible privacy-preserving data analysis techniques. It proposes developing key theorems to analyze what types of privacy-preserving data analysis tasks can be conducted such that providing truthful private inputs is in each party's best interest. Existing techniques cannot verify truthful inputs, but this approach aims to make truthfulness the rational choice through game theoretic analysis of tasks like association rule mining on horizontally and vertically partitioned databases.
Enhancing access privacy of range retrievals over b+treesMigrant Systems
The document proposes a new index structure called PB+tree to enhance privacy for range queries over encrypted B+trees. It first shows that an adversary can infer the structure of an encrypted B+tree and query ranges by observing I/O patterns of range queries. PB+tree aims to conceal the ordering of leaf nodes by grouping nodes into buckets and using homomorphic encryption to obscure which exact nodes are retrieved. It balances privacy with computational overhead. Experiments show PB+tree effectively impairs the adversary's ability to deduce the B+tree structure and query ranges.
Incentive Compatible Privacy Preserving Data Analysisrupasri mupparthi
Now a days, data management applications have evolved from pure storage and retrieval of information to finding interesting patterns and associations from large amounts of data. With the advancement of Internet and networking technologies, more and more computing applications, including data mining programs, are required to be conducted among multiple data sources that scattered around different spots, and to jointly conduct the computation to reach a common result. However, due to legal constraints and competition edges, privacy issues arise in the area of distributed data mining, thus leading to the interests from research community of both data mining.
In this project each party participates in a protocol to learn the output of some function f over the joint inputs of the parties. We mainly focus on the DNCC model instead of considering a probabilistic extension. Deterministic Non Cooperative Computation needs to be extended to include the possibility of collusion.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
This document discusses privacy concerns when collaboratively publishing horizontally partitioned data from multiple data providers. It introduces the concept of an "m-adversary", which is a group of up to m colluding data providers. It also introduces the notion of "m-privacy", which guarantees anonymity against such m-adversaries. The paper then presents algorithms for efficiently checking m-privacy while maximizing data utility and handling different m-adversary attack scenarios. Experiments on real datasets show the approach achieves better utility and efficiency than existing methods while providing m-privacy guarantees.
A Rule based Slicing Approach to Achieve Data Publishing and Privacyijsrd.com
several anonymization techniques, such as generalization and bucketization, have been designed for privacy preserving micro data publishing. Recent work has shown that generalization loses considerable amount of information, especially for high dimensional data. Bucketization, on the other hand, does not prevent membership disclosure and does not apply for data that do not have a clear separation between quasi-identifying attributes and sensitive attributes. The existing system proposed slicing concept to overcome the tuple based partition this has been done to overcome the previous generalization and bucketization. In this paper, present a novel technique called rule based slicing, which partitions the data both horizontally and vertically. We show that slicing preserves better data utility than generalization and can be used for membership disclosure protection. Another important advantage of slicing is that it can handle high-dimensional data. We show how slicing can be used for attribute disclosure protection and develop an efficient algorithm for computing the sliced data that obey the l-diversity requirement. The workload experiments confirm that slicing preserves better utility than generalization and is more effective than bucketization in workloads involving the sensitive attribute. The experiments also demonstrate that slicing can be used to prevent membership disclosure
Advanced SQL covers selecting columns, aggregate functions like MIN() and MAX(), the CASE WHEN statement, JOINs, the WHERE clause, GROUP BY, declaring variables, and subqueries
- AtomicDB uses a vector space model to represent data as interconnected informational elements at the center of their relationship universes, allowing each data item to act as an entry point into the network.
- Associations in AtomicDB are bidirectional references between data items, with no separate connector or predicate items. The algorithm that determines associations is entirely fact-based.
- Large datasets can be distributed across multiple servers by mapping data element tokens to different physical locations on contingent high-bandwidth networks.
The document discusses incentive compatible privacy-preserving data analysis techniques. It proposes developing key theorems to analyze what types of privacy-preserving data analysis tasks can be conducted such that providing truthful private inputs is in each party's best interest. Existing techniques cannot verify truthful inputs, but this approach aims to make truthfulness the rational choice through game theoretic analysis of tasks like association rule mining on horizontally and vertically partitioned databases.
Enhancing access privacy of range retrievals over b+treesMigrant Systems
The document proposes a new index structure called PB+tree to enhance privacy for range queries over encrypted B+trees. It first shows that an adversary can infer the structure of an encrypted B+tree and query ranges by observing I/O patterns of range queries. PB+tree aims to conceal the ordering of leaf nodes by grouping nodes into buckets and using homomorphic encryption to obscure which exact nodes are retrieved. It balances privacy with computational overhead. Experiments show PB+tree effectively impairs the adversary's ability to deduce the B+tree structure and query ranges.
Incentive Compatible Privacy Preserving Data Analysisrupasri mupparthi
Now a days, data management applications have evolved from pure storage and retrieval of information to finding interesting patterns and associations from large amounts of data. With the advancement of Internet and networking technologies, more and more computing applications, including data mining programs, are required to be conducted among multiple data sources that scattered around different spots, and to jointly conduct the computation to reach a common result. However, due to legal constraints and competition edges, privacy issues arise in the area of distributed data mining, thus leading to the interests from research community of both data mining.
In this project each party participates in a protocol to learn the output of some function f over the joint inputs of the parties. We mainly focus on the DNCC model instead of considering a probabilistic extension. Deterministic Non Cooperative Computation needs to be extended to include the possibility of collusion.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Data and Computation Interoperability in Internet ServicesSergey Boldyrev
This document discusses the need for a framework to enable interoperability between heterogeneous cloud infrastructures and systems. It proposes representing data and computation semantically so they can be transmitted and executed across different environments. It also emphasizes the importance of analyzing system behavior and performance to achieve accountability and manage privacy, security, and latency requirements in distributed cloud systems.
1. A database is a set of organized and interrelated data collected by a business to be accessed through software. It allows data to be entered, stored, and retrieved in an easy-to-access manner.
2. Database management systems (DBMS) are software programs that allow users to create, access, organize, share, and manage data efficiently. They provide independence between data and applications, easier data manipulation, security, integrity and structure to databases.
3. Users can query databases to retrieve, add, update and delete information. Query languages allow users to issue commands to the DBMS to access and manipulate data stored in databases.
survey paper on object oriented cryptographic security for runtime entitiesINFOGAIN PUBLICATION
With the advent of complex systems the need for large data storage with less space utility & high performance have become the vital features. Another important concern of the data is the security which is assured via the cryptographic techniques implemented at all levels of data storage. In this survey paper we introduce the concept of security between two hierarchical data accesses and propose the concept of hierarchical cryptography between data of different classes of different hierarchies.
This white paper proposes a concept called "Data Convergence" to provide a unified view of open government datasets from different sources and formats. The solution would build a software application with an HTTP API to integrate datasets and identify relationships between them based on common attributes. This would allow users to more easily analyze linked datasets and derive useful information. The benefits of this approach include easy access to real-time converged data through standard JSON/XML formats with loose coupling between the underlying data storage and applications.
A Non-Technical, Example-Driven Introduction to Linked Datakjanowicz
How Linked Data and Semantic Web Technologies Foster the Publication, Retrieval, Reuse, and Integration of Data. A Non-Technical, Example-Driven Introduction to Linked Data for the UCSB Library.
CONTROL CLOUD DATA ACCESS PRIVILEGE AND ANONYMITY WITH FULLY ANONYMOUS ATTRIB...Nexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
A Study of Usability-aware Network Trace Anonymization Kato Mivule
This document summarizes research on anonymizing network trace data while maintaining usability. It discusses challenges in applying traditional anonymization techniques to network traces due to their unique structure. The paper proposes heuristics for usability-aware anonymization that apply microdata privacy techniques separately to different network trace attributes. Preliminary results suggest the potential to generate anonymized traces with improved usability through trade-offs determined on a case-by-case basis. The document also reviews related work on network trace anonymization and attacks against anonymized data.
Data Integration in Multi-sources Information Systemsijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Control cloud data access privilege andjpstudcorner
The document proposes two schemes, AnonyControl and AnonyControl-F, to control access privileges for cloud data while protecting user identity privacy. Existing schemes focus on access control and data privacy but reveal user identities. The proposed schemes decentralize authorities so each knows only attributes, preventing identity discovery. AnonyControl provides semi-anonymity while AnonyControl-F fully prevents identity leakage. The schemes allow fine-grained privilege management and remain secure if fewer than N-2 of N authorities are compromised.
AELA is an adaptive entity linking approach consisting of five modules that allows entity linking to be performed across different linked data datasets with varying schemas. The first module selects a suitable linked data dataset based on domain and quality. The second module adapts to the dataset schema by identifying entity classes and name properties. The third module generates a gazetteer from the dataset. The fourth module recognizes entity mentions in text. The fifth module disambiguates entities by linking mentions to candidates using a graph-based method. Evaluation shows the system achieves high precision, recall and F-score on music and movie datasets.
INFORMATION-CENTRIC BLOCKCHAIN TECHNOLOGY FOR THE SMART GRIDIJNSA Journal
This paper proposes an application of blockchain technology for securing the infrastructure of the modern power grid - an Information-Centric design for the blockchain network. In this design, all the transactions in the blockchain network are classified into different groups, and each group has a group number. A sender’s identity is encrypted by the control centre’s public key; energy data is encrypted by the subscriber’s public key, and by a receiver’s public key if this transaction is for a specific receiver; a valid signature is created via a group message and the group publisher’s private key. Our implementation of the design demonstrated the proposal is applicable, publisher’s identities are protected, data sources are hidden, data privacy is maintained, and data consistency is preserved.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document proposes a scheme called PRMSM that enables privacy-preserving ranked multi-keyword search on encrypted cloud data from multiple data owners. It constructs a secure search protocol that allows cloud servers to perform searches without knowing the actual data or trapdoors. It also proposes a novel function to preserve the privacy of relevance scores between keywords and files during ranking. The scheme supports dynamic key generation, user authentication, and efficient user revocation to enhance security. Experiments show the efficacy and efficiency of PRMSM.
This document discusses searchable encryption systems and the current state of data security. It covers common uses of encryption like SSL and describes limitations of early encryption methods like Yao's Garbled Circuits. The document then focuses on fully homomorphic encryption, which allows computations on encrypted data without decrypting it first. While promising, homomorphic encryption has limitations in speed and potential security issues that require more research to address.
The document discusses knowledge discovery and data mining. It describes knowledge discovery as automatically searching large volumes of data for patterns that can be considered knowledge. The document outlines the five steps of the knowledge discovery process and notes it is closely related to data mining. It then discusses data mining, describing the purpose, preference, and search techniques used in data mining algorithms. The document also categorizes data mining and describes how it provides links between transactional and analytical systems to analyze relationships and patterns in stored data.
Computer encryption uses cryptography to securely transmit sensitive information over the internet. There are two main types of encryption: symmetric key encryption where both computers share the same secret key, and public key encryption which addresses weaknesses of symmetric key by allowing users to communicate securely without pre-sharing a key. Popular implementations of public key encryption include Secure Sockets Layer (SSL) and Transport Layer Security (TLS) protocols used to transmit encrypted web traffic. Hashing algorithms also play a key role in public key encryption by generating unique hash values from data that cannot be reversed without the original input, improving security.
Objectives
What is Encapsulation?
What encapsulation or information hiding approach provide in Object Oriented ?
General 3 different ways to Encapsulate data.
Advantages of Encapsulation.
Multi-dimensional cubic symmetric block cipher algorithm for encrypting big datajournalBEEI
The advanced technology in the internet and social media, communication companies, health care records and cloud computing applications made the data around us increase dramatically every minute and continuously. These renewals big data involve sensitive information such as password, PIN number, credential numbers, secret identifications and etc. which require maintaining with some high secret procedures. The present paper involves proposing a secret multi-dimensional symmetric cipher with six dimensions as a cubic algorithm. The proposed algorithm works with the substitution permutation network (SPN) structure and supports a high processing data rate in six directions. The introduced algorithm includes six symmetry rounds transformations for encryption the plaintext, where each dimension represents an independent algorithm for big data manipulation. The proposed cipher deals with parallel encryption structures of the 128-bit data block for each dimension in order to handle large volumes of data. The submitted cipher compensates for six algorithms working simultaneously each with 128-bit according to various irreducible polynomials of order eight. The round transformation includes four main encryption stages where each stage with a cubic form of six dimensions.
In this era, there are need to secure data in distributed database system. For collaborative data
publishing some anonymization techniques are available such as generalization and bucketization. We consider
the attack can call as “insider attack” by colluding data providers who may use their own records to infer
others records. To protect our database from these types of attacks we used slicing technique for anonymization,
as above techniques are not suitable for high dimensional data. It cause loss of data and also they need clear
separation of quasi identifier and sensitive database. We consider this threat and make several contributions.
First, we introduce a notion of data privacy and used slicing technique which shows that anonymized data
satisfies privacy and security of data which classifies data vertically and horizontally. Second, we present
verification algorithms which prove the security against number of providers of data and insure high utility and
data privacy of anonymized data with efficiency. For experimental result we use the hospital patient datasets
and suggest that our slicing approach achieves better or comparable utility and efficiency than baseline
algorithms while satisfying data security. Our experiment successfully demonstrates the difference between
computation time of encryption algorithm which is used to secure data and our system.
Cloud assisted mobile-access of health data with privacy and auditabilityIGEEKS TECHNOLOGIES
The document proposes a cloud-assisted mobile health system with privacy and auditability. It introduces using a private cloud to store and process health data, with cryptographic mechanisms like searchable symmetric encryption, identity-based encryption, and attribute-based encryption to provide privacy. This includes hiding search and access patterns. The system also allows for auditing of emergency data access. The proposed architecture and modules are described, including key management, secure indexing, and role-based access control with auditing functionality.
This document summarizes a research paper on secured authorized deduplication in a hybrid cloud system. The system aims to provide data deduplication, differential authorization for access, and confidentiality of data files. It involves a public cloud for storage, a private cloud for managing access tokens, and users who generate keys for files stored on the public cloud. When uploading a file, the user encrypts it and sends it to the public cloud along with the key to the private cloud. To download, the user must provide the correct key to the private cloud to gain access to encrypted files from the public cloud. This hybrid cloud model uses deduplication for storage optimization while controlling access through differential authorization of private keys.
Data and Computation Interoperability in Internet ServicesSergey Boldyrev
This document discusses the need for a framework to enable interoperability between heterogeneous cloud infrastructures and systems. It proposes representing data and computation semantically so they can be transmitted and executed across different environments. It also emphasizes the importance of analyzing system behavior and performance to achieve accountability and manage privacy, security, and latency requirements in distributed cloud systems.
1. A database is a set of organized and interrelated data collected by a business to be accessed through software. It allows data to be entered, stored, and retrieved in an easy-to-access manner.
2. Database management systems (DBMS) are software programs that allow users to create, access, organize, share, and manage data efficiently. They provide independence between data and applications, easier data manipulation, security, integrity and structure to databases.
3. Users can query databases to retrieve, add, update and delete information. Query languages allow users to issue commands to the DBMS to access and manipulate data stored in databases.
survey paper on object oriented cryptographic security for runtime entitiesINFOGAIN PUBLICATION
With the advent of complex systems the need for large data storage with less space utility & high performance have become the vital features. Another important concern of the data is the security which is assured via the cryptographic techniques implemented at all levels of data storage. In this survey paper we introduce the concept of security between two hierarchical data accesses and propose the concept of hierarchical cryptography between data of different classes of different hierarchies.
This white paper proposes a concept called "Data Convergence" to provide a unified view of open government datasets from different sources and formats. The solution would build a software application with an HTTP API to integrate datasets and identify relationships between them based on common attributes. This would allow users to more easily analyze linked datasets and derive useful information. The benefits of this approach include easy access to real-time converged data through standard JSON/XML formats with loose coupling between the underlying data storage and applications.
A Non-Technical, Example-Driven Introduction to Linked Datakjanowicz
How Linked Data and Semantic Web Technologies Foster the Publication, Retrieval, Reuse, and Integration of Data. A Non-Technical, Example-Driven Introduction to Linked Data for the UCSB Library.
CONTROL CLOUD DATA ACCESS PRIVILEGE AND ANONYMITY WITH FULLY ANONYMOUS ATTRIB...Nexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
A Study of Usability-aware Network Trace Anonymization Kato Mivule
This document summarizes research on anonymizing network trace data while maintaining usability. It discusses challenges in applying traditional anonymization techniques to network traces due to their unique structure. The paper proposes heuristics for usability-aware anonymization that apply microdata privacy techniques separately to different network trace attributes. Preliminary results suggest the potential to generate anonymized traces with improved usability through trade-offs determined on a case-by-case basis. The document also reviews related work on network trace anonymization and attacks against anonymized data.
Data Integration in Multi-sources Information Systemsijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Control cloud data access privilege andjpstudcorner
The document proposes two schemes, AnonyControl and AnonyControl-F, to control access privileges for cloud data while protecting user identity privacy. Existing schemes focus on access control and data privacy but reveal user identities. The proposed schemes decentralize authorities so each knows only attributes, preventing identity discovery. AnonyControl provides semi-anonymity while AnonyControl-F fully prevents identity leakage. The schemes allow fine-grained privilege management and remain secure if fewer than N-2 of N authorities are compromised.
AELA is an adaptive entity linking approach consisting of five modules that allows entity linking to be performed across different linked data datasets with varying schemas. The first module selects a suitable linked data dataset based on domain and quality. The second module adapts to the dataset schema by identifying entity classes and name properties. The third module generates a gazetteer from the dataset. The fourth module recognizes entity mentions in text. The fifth module disambiguates entities by linking mentions to candidates using a graph-based method. Evaluation shows the system achieves high precision, recall and F-score on music and movie datasets.
INFORMATION-CENTRIC BLOCKCHAIN TECHNOLOGY FOR THE SMART GRIDIJNSA Journal
This paper proposes an application of blockchain technology for securing the infrastructure of the modern power grid - an Information-Centric design for the blockchain network. In this design, all the transactions in the blockchain network are classified into different groups, and each group has a group number. A sender’s identity is encrypted by the control centre’s public key; energy data is encrypted by the subscriber’s public key, and by a receiver’s public key if this transaction is for a specific receiver; a valid signature is created via a group message and the group publisher’s private key. Our implementation of the design demonstrated the proposal is applicable, publisher’s identities are protected, data sources are hidden, data privacy is maintained, and data consistency is preserved.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
This document proposes a scheme called PRMSM that enables privacy-preserving ranked multi-keyword search on encrypted cloud data from multiple data owners. It constructs a secure search protocol that allows cloud servers to perform searches without knowing the actual data or trapdoors. It also proposes a novel function to preserve the privacy of relevance scores between keywords and files during ranking. The scheme supports dynamic key generation, user authentication, and efficient user revocation to enhance security. Experiments show the efficacy and efficiency of PRMSM.
This document discusses searchable encryption systems and the current state of data security. It covers common uses of encryption like SSL and describes limitations of early encryption methods like Yao's Garbled Circuits. The document then focuses on fully homomorphic encryption, which allows computations on encrypted data without decrypting it first. While promising, homomorphic encryption has limitations in speed and potential security issues that require more research to address.
The document discusses knowledge discovery and data mining. It describes knowledge discovery as automatically searching large volumes of data for patterns that can be considered knowledge. The document outlines the five steps of the knowledge discovery process and notes it is closely related to data mining. It then discusses data mining, describing the purpose, preference, and search techniques used in data mining algorithms. The document also categorizes data mining and describes how it provides links between transactional and analytical systems to analyze relationships and patterns in stored data.
Computer encryption uses cryptography to securely transmit sensitive information over the internet. There are two main types of encryption: symmetric key encryption where both computers share the same secret key, and public key encryption which addresses weaknesses of symmetric key by allowing users to communicate securely without pre-sharing a key. Popular implementations of public key encryption include Secure Sockets Layer (SSL) and Transport Layer Security (TLS) protocols used to transmit encrypted web traffic. Hashing algorithms also play a key role in public key encryption by generating unique hash values from data that cannot be reversed without the original input, improving security.
Objectives
What is Encapsulation?
What encapsulation or information hiding approach provide in Object Oriented ?
General 3 different ways to Encapsulate data.
Advantages of Encapsulation.
Multi-dimensional cubic symmetric block cipher algorithm for encrypting big datajournalBEEI
The advanced technology in the internet and social media, communication companies, health care records and cloud computing applications made the data around us increase dramatically every minute and continuously. These renewals big data involve sensitive information such as password, PIN number, credential numbers, secret identifications and etc. which require maintaining with some high secret procedures. The present paper involves proposing a secret multi-dimensional symmetric cipher with six dimensions as a cubic algorithm. The proposed algorithm works with the substitution permutation network (SPN) structure and supports a high processing data rate in six directions. The introduced algorithm includes six symmetry rounds transformations for encryption the plaintext, where each dimension represents an independent algorithm for big data manipulation. The proposed cipher deals with parallel encryption structures of the 128-bit data block for each dimension in order to handle large volumes of data. The submitted cipher compensates for six algorithms working simultaneously each with 128-bit according to various irreducible polynomials of order eight. The round transformation includes four main encryption stages where each stage with a cubic form of six dimensions.
In this era, there are need to secure data in distributed database system. For collaborative data
publishing some anonymization techniques are available such as generalization and bucketization. We consider
the attack can call as “insider attack” by colluding data providers who may use their own records to infer
others records. To protect our database from these types of attacks we used slicing technique for anonymization,
as above techniques are not suitable for high dimensional data. It cause loss of data and also they need clear
separation of quasi identifier and sensitive database. We consider this threat and make several contributions.
First, we introduce a notion of data privacy and used slicing technique which shows that anonymized data
satisfies privacy and security of data which classifies data vertically and horizontally. Second, we present
verification algorithms which prove the security against number of providers of data and insure high utility and
data privacy of anonymized data with efficiency. For experimental result we use the hospital patient datasets
and suggest that our slicing approach achieves better or comparable utility and efficiency than baseline
algorithms while satisfying data security. Our experiment successfully demonstrates the difference between
computation time of encryption algorithm which is used to secure data and our system.
Cloud assisted mobile-access of health data with privacy and auditabilityIGEEKS TECHNOLOGIES
The document proposes a cloud-assisted mobile health system with privacy and auditability. It introduces using a private cloud to store and process health data, with cryptographic mechanisms like searchable symmetric encryption, identity-based encryption, and attribute-based encryption to provide privacy. This includes hiding search and access patterns. The system also allows for auditing of emergency data access. The proposed architecture and modules are described, including key management, secure indexing, and role-based access control with auditing functionality.
This document summarizes a research paper on secured authorized deduplication in a hybrid cloud system. The system aims to provide data deduplication, differential authorization for access, and confidentiality of data files. It involves a public cloud for storage, a private cloud for managing access tokens, and users who generate keys for files stored on the public cloud. When uploading a file, the user encrypts it and sends it to the public cloud along with the key to the private cloud. To download, the user must provide the correct key to the private cloud to gain access to encrypted files from the public cloud. This hybrid cloud model uses deduplication for storage optimization while controlling access through differential authorization of private keys.
Secured Authorized Deduplication Based Hybrid Cloudtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
A Review on Key-Aggregate Cryptosystem for Climbable Knowledge Sharing in Clo...Editor IJCATR
The Data sharing is an important functionality in cloud storage. In this article, we show how to securely, efficiently, and
flexibly share data with others in cloud storage. We describe new public-key cryptosystems which produce constant-size ciphertexts
such that efficient delegation of decryption rights for any set of ciphertexts are possible. The novelty is that one can aggregate any set
of secret keys and make them as compact as a single key, but encompassing the power of all the keys being aggregated. In other
words, the secret key holder can release a constant-size aggregate key for flexible choices of ciphertext set in cloud storage, but the
other encrypted files outside the set remain confidential. This compact aggregate key can be conveniently sent to others or be stored in
a smart card with very limited secure storage. We provide formal security analysis of our schemes in the standard model. We also
describe other application of our schemes. In particular, our schemes give the first public-key patient controlled encryption for flexible
hierarchy, which was yet to be known.
Abstract-The current trend in the application space towards systems of loosely coupled and dynamically bound components that enables just-in-time integration jeopardizes the security of information that is shared between the broker, the requester, and the provider at runtime. In particular, new advances in data mining and knowledge discovery that allow for the extraction of hidden knowledge in an enormous amount of data impose new threats on the seamless integration of information. We consider the problem of building privacy preserving algorithms for one category of data mining techniques, association rule mining.Suppose Alice owns a k-anonymous database and needs to determine whether her database, when inserted with a tuple owned by Bob, is still k-anonymous. Also, suppose that access to the database is strictly controlled, because for example data are used for certain experiments that need to be maintained confidential. Clearly, allowing Alice to directly read the contents of the tuple breaks the privacy of Bob (e.g., a patient’s medical record); on the other hand, the confidentiality of the database managed by Alice is violated once Bob has access to the contents of the database. Thus, the problem is to check whether the database inserted with the tuple is still k-anonymous, without letting Alice and Bob know the contents of the tuple and the database, respectively. In this paper, we propose two protocols solving this problem on suppression-based and generalization-based k-anonymous and confidential databases. The protocols rely on well-known cryptographic assumptions, and we provide theoretical analyses to proof their soundness and experimental results to illustrate their efficiency.We have presented two secure protocols for privately checking whether a k-anonymous database retains its anonymity once a new tuple is being inserted to it. Since the proposed protocols ensure the updated database remains K-anonymous, the results returned from a user’s (or a medical researcher’s) query are also k-anonymous. Thus, the patient or the data provider’s privacy cannot be violated from any query. As long as the database is updated properly using the proposed protocols, the user queries under our application domain are always privacy-preserving.
Privacy-Preserving Updates to Anonymous and Confidential Databaseijdmtaiir
The current trend in the application space towards
systems of loosely coupled and dynamically bound
components that enables just-in-time integration jeopardizes
the security of information that is shared between the broker,
the requester, and the provider at runtime. In particular, new
advances in data mining and knowledge discovery that allow
for the extraction of hidden knowledge in an enormous amount
of data impose new threats on the seamless integration of
information. We consider the problem of building privacy
preserving algorithms for one category of data mining
techniques, association rule mining.Suppose Alice owns a kanonymous database and needs to determine whether her
database, when inserted with a tuple owned by Bob, is still kanonymous. Also, suppose that access to the database is strictly
controlled, because for example data are used for certain
experiments that need to be maintained confidential. Clearly,
allowing Alice to directly read the contents of the tuple breaks
the privacy of Bob (e.g., a patient’s medical record); on the
other hand, the confidentiality of the database managed by
Alice is violated once Bob has access to the contents of the
database. Thus, the problem is to check whether the database
inserted with the tuple is still k-anonymous, without letting
Alice and Bob know the contents of the tuple and the database,
respectively. In this paper, we propose two protocols solving
this problem on suppression-based and generalization-based kanonymous and confidential databases. The protocols rely on
well-known cryptographic assumptions, and we provide
theoretical analyses to proof their soundness and experimental
results to illustrate their efficiency.We have presented two
secure protocols for privately checking whether a kanonymous database retains its anonymity once a new tuple is
being inserted to it. Since the proposed protocols ensure the
updated database remains K-anonymous, the results returned
from a user’s (or a medical researcher’s) query are also kanonymous. Thus, the patient or the data provider’s privacy
cannot be violated from any query. As long as the database is
updated properly using the proposed protocols, the user queries
under our application domain are always privacy-preserving
Messages addressed to specific users can be decrypted by Key Generation Centre (KGC) by generating their private keys. Data owner wants the data to be delivered only to specified user and not to unauthorized person that is the data owner makes their private data accessible only to authorized person. We propose attribute based encryption and escrow problem which means written agreement delivered to a third party to overcome this problem. Attribute based Encryption (ABE) is a type of public-key encryption in which the private key of a user and the cipher text are dependent upon attributes. It is a promising cryptographic approach.
Implementation of De-Duplication AlgorithmIRJET Journal
The document describes an implementation of a data de-duplication algorithm using convergent encryption. It discusses how data de-duplication works to reduce storage usage by identifying and removing duplicate copies of data. Convergent encryption is used, which generates the same encrypted form of a file from the original file's hash, allowing duplicate encrypted files to be de-duplicated while preserving privacy. The algorithm divides files into blocks, generates hashes for each block, and encrypts the file blocks using the hashes as keys. When a file is uploaded, its hash is checked against existing hashes to identify duplicates, with duplicates replaced by pointers to the stored copy. This allows efficient de-duplication while encrypting data for privacy and security when stored
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The document proposes a privacy-preserving mobile healthcare system using a private cloud. It aims to address privacy issues with electronic healthcare by building privacy into the system. The key features include efficient key management, privacy-preserving data storage and retrieval (especially for emergencies), and auditability to prevent misuse of health data. The system utilizes techniques like searchable symmetric encryption, identity-based encryption and attribute-based encryption for security. It follows a cloud-assisted service model with the private cloud storing and processing data to support lightweight tasks on mobile devices.
Iaetsd enhancement of performance and security in bigdata processingIaetsd Iaetsd
This document discusses enhancing performance and security in big data processing. It proposes collecting sensitive data and encrypting it using proxy re-encryption before storing it in a NoSQL database for increased security. The encrypted data can then be decrypted and accessed by authorized external users. MapReduce is used to filter duplicate data during access.
1. The document proposes a system for secure user authentication and access control for encrypted data stored in the cloud. It aims to address issues with centralized access control and storing data in plaintext.
2. The proposed system uses a key distribution center to generate public, private, and access keys for authentication at different levels. Data is encrypted before being fragmented and distributed across multiple servers.
3. Only authorized users with proper keys can decrypt the data. Access policies set by data creators restrict which users can access files. Storing encrypted and distributed data along with key-based authentication aims to improve security over existing cloud storage systems.
Secure Data Sharing Algorithm for Data Retrieval In Military Based NetworksIJTET Journal
Abstract— Mobile knots now armed atmospheres such equally battlefield or aggressive area remain expected toward smart after irregular net connectivity and regular panels. Disruption Tolerant Network (DTN) tools stay attractive positive keys that agree knots toward connect with each other in these dangerous interacting atmospheres.The problem of applying the security mechanisms to DTN introduces several security challenges.Since nearly handlers could modification their related characteristics by approximately argument and reliability of data should be changed otherwise around isolated secrets power remain bargained significant reversal aimed at respectively characteristic is essential in command toward create organisms safe in this research a novel approaches are used to overcome the above mentioned problems called secure data sharing algorithm. This algorithm calculate hash importance aimed at coded documents which is used to check the reliability of encrypted confidential data.
Key aggregate searchable encryption (kase) for group data sharing via cloud s...CloudTechnologies
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Improving Efficiency of Security in Multi-CloudIJTET Journal
Abstract--Due to risk in service availability failure and the possibilities of malicious insiders in the single cloud, a movement towards “Multi-clouds” has emerged recently. In general a multi-cloud security system there is a possibility for third party to access the user files. Ensuring security in this stage has become tedious since, most of the activities are done in network. In this paper, an enhanced security methodology has been introduced in order to make the data stored in cloud more secure. Duple authentication process introduced in this concept defends malicious insiders and shields the private data. Various disadvantages in traditional systems like unauthorized access, hacking have been overcome in this proposed system and a comparison made with the traditional systems in terms of performance and computational time have shown better results.
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What will you get from this session?
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3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
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Overview
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JAVA 2013 IEEE NETWORKSECURITY PROJECT Utility privacy tradeoff in databases an information-theoretic approach
1. Utility-Privacy Tradeoff in Databases An Information-
theoretic Approach
Abstract:
Ensuring the usefulness of electronic data sources while providing necessary
privacy guarantees is an important unsolved problem. This problem drives the
need for an analytical framework that can quantify the privacy of personally
identifiable information while still providing a quantifable benefit (utility) to
multiple legitimate information consumers. This paper presents an information-
theoretic framework that promises an analytical model guaranteeing tight bounds
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contributions include: i) stochastic data models for both categorical and numerical
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2. Architecture:
EXISTING SYSTEM:
We divide the existing work into two categories, heuristic and theoretical
techniques, and outline the major milestones from these categories for
comparison. The earliest attempts at systematic privacy were in the area of census
data publication where data was required to be made public but without leaking
individuals’ information. A number of ad hoc techniques such as sub-sampling,
aggregation, and suppression were explored. The first formal definition of privacy
was k-anonymity by Sweeney. However k-anonymity was found to be inadequate
as it only protects from identity disclosure but not attribute-based disclosure and
was extended with t-closeness and l-diversity . All these techniques have proved
to be non-universal as they were only robust against limited adversaries. Heuristic
techniques for privacy in data mining have focused on using a mutual information-
based privacy metrics.
3. PROPOSED SYSTEM:
Our work is based on the observation that large datasets (including databases)
have a distributional basis; i.e., there exists an underlying (sometimes implicit)
statistical model for the data. Even in the case Of data mining where only one or a
few instances of the dataset are ever available, the use of correlations between
attributes used an implicit distributional assumption about the dataset. We
explicitly model the data as being generated by a source with a finite or infinite
alphabet and a known distribution. Each row of the database is a collection of
correlated attributes (of an individual) that belongs to the alphabet of the source
and is generated according to the probability of occurrence of that letter (of the
alphabet). Our statistical model for databases is also motivated by the fact that
while the attributes of an individual may be correlated, the records of a large
number of individuals are generally independent or weakly correlated with each
other. We thus model the database as a collection of n observations generated by
a memory less source whose outputs are independent and identically distributed.
Modules :
1. Registration
2. Login
3. Admin
4. Encryption and Decryption
5. Chart_view
Modules Description
Registration:
In this module Sender/User have to register first, then only
he/she has to access the data base.
4. Login:
In this module, any of the above mentioned person
have to login, they should login by giving their email id and password .Admin login
by giving username and password.
Admin:
Admin can see the details of the people who are published their personal
data. Data are in encrypted form. He then decrypt it by using decryption and then
only he will be able to see the original data
Encryption and Decryption Java Code:
public class EBCDIC
{
public static void main(String arg[])
{
EBCDIC a=new EBCDIC();
System.out.println("EBCDIC: " + a.decrypt(a.encrypt("abcdhello")));
}
public static String encrypt(String str)
{
byte b[] = new byte[str.length()];
byte result[] = new byte[str.length()];
6. }
return ( new String(result) );
}
}
Chart_View:
The Receiver can only view the senders personal data by pictorial
representation i.e chart.Chart will be prepared by applying the senders input.Also
he can see the personal data in encrypted form.Registered users only can decrypt
the data.We hide the correct income of the senders who pass the data to
receivers.Receivers will be able to see the actual income of senders by applying
some side informations.
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
7. 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.
Database : My sql
Database Connectivity : JDBC.
Conclusion:
The ability to achieve the desired level of privacy while guaranteeing
a minimal level of utility and vice-versa for a general data source is paramount.
Our work defines privacy and utility as fundamental characteristics of data sources
that may be in conflict and can be traded off. This is one of the earliest attempts at
systematically applying information theoretic techniques to this problem. Using
rate-distortion theory, we have developed a U-P tradeoff region for i.i.d. data
sources with known distribution.