The document discusses using anonymous identity assignment (AIDA) to preserve privacy and security when sharing data across distributed systems. AIDA allows nodes in a network to be assigned anonymous IDs through a distributed computation, so their real identities are unknown to other nodes. This allows sensitive data to be shared anonymously. The document outlines existing approaches like using a trusted third party and secure multi-party computation, and their limitations. It then proposes using AIDA and secure computations to allow private queries and sharing of complex data while preserving anonymity of nodes. Experimental results show the approach can anonymously store and retrieve patient medical records.
Ijeee 7-11-privacy preserving distributed data mining with anonymous id assig...Kumar Goud
Privacy Preserving Distributed Data Mining with Anonymous ID Assignment
Chikkudu Chandrakanth Bheemari Santhoshkumar Tejavath Charan Singh
M.Tech Scholar(CSE) M.Tech Scholar(CSE) Assistant Professor, Dept of CSE
Sri Indu College of Engg and Tech Sri Indu College of Engg and Tech Sri Indu College of Engg and Tech
Ibrahimpatan, Hyderabad, TS, India Ibrahimpatan, Hyderabad, TS, India Ibrahimpatan, Hyderabad, TS, India
Abstract: This paper builds an algorithm for sharing simple integer data on top of secure sum data mining operation using Newton’s identities and Sturm’s theorem. Algorithm for anonymous sharing of private data among parties is developed. This assignment is anonymous in that the identities received are unknown to the other members of the group. Resistance to collusion among other members is verified in an information theoretic sense when private communication channels are used. This assignment of serial numbers allows more complex data to be shared and has applications to other problems in privacy preserving data mining, collision avoidance in communications and distributed database access. The new algorithms are built on top of a secure sum data mining operation using Newton’s identities and Sturm’s theorem. An algorithm for distributed solution of certain polynomials over finite fields enhances the scalability of the algorithms.
Key words: Cloud, Website, information sharing, DBMS, ID, ODBC, ASP.NET
.
Privacy Preservation And Data Security In Location Based ServicesEditorJST
This document summarizes a research paper about preserving privacy and security in location-based services. It proposes a two-stage approach using oblivious transfer and a data retrieval phase to allow a user to query a database without revealing their identity or location to the server. The data on the server is encrypted for security. An intermediate service provider acts as a trusted third party to facilitate the private queries. If data is attacked, it can be recovered from a secondary server using message authentication codes to detect changes. The goal is to let users access location data privately while also protecting the server's data.
Modeling and Detection of Data Leakage FraudIOSR Journals
This document proposes strategies for detecting data leakage when sensitive data is distributed through trusted agents. It aims to detect leakage without modifying the original data objects. The key strategies are to personalize data objects for each agent by mixing in fake objects that contain the agent's identity. When objects are leaked, the distributor can use the fake objects to detect leakage and identify the guilty agent. The strategies were tested with a prototype application and showed to be effective for real-time leakage detection and agent identification without changing the original data objects.
The document describes a privacy-preserving method for detecting inadvertent leaks of sensitive data in network traffic. The method allows an organization to outsource detection to a provider without revealing the actual sensitive data. It involves the organization computing digests of the sensitive data and sharing a sample with the provider. The provider searches traffic for matches and returns potential leaks. The organization then determines if any are true leaks, protecting the privacy of the sensitive data from the provider. The method was implemented and evaluated on real datasets, showing accurate detection while preserving privacy.
GDPR BigDataRevealed Readiness Requirements and EvaluationSteven Meister
This GDPR methodology can evaluate your GDPR readiness. For those feeling GDPR ready, you may uncover complex issues often neglected. For those that have waited, you can gain knowledge providing for a more successful GDPR outcome.
https://youtu.be/uE4Q7u0LatU https://youtu.be/R37S9mIiVAk https://youtu.be/AQf3if7DnuM
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
Interplay of Digital Forensics in eDiscoveryCSCJournals
Digital forensics is often confused with eDiscovery (electronic discovery). However, both the fields are highly independent of the other but slightly overlap to assist each other in a symbiotic relationship. With decreasing costs of cloud storage, growing Internet speeds, and growing capacity of portable storage media, their chances of being used in a crime have grown. Sifting through large volumes of evidential data during eDiscovery or forensically investigating them requires teams from both these fields to work together on a case. In this paper, the authors discuss the relationship between these disciplines and highlight the digital forensic skills required, sub-disciplines of digital forensics, the possible electronic artifacts that can be encountered in a case, and the forensic opportunities relative to the eDiscovery industry. Lastly, the authors touch upon the best practices in digital evidence management during the eDiscovery process.
Ijeee 7-11-privacy preserving distributed data mining with anonymous id assig...Kumar Goud
Privacy Preserving Distributed Data Mining with Anonymous ID Assignment
Chikkudu Chandrakanth Bheemari Santhoshkumar Tejavath Charan Singh
M.Tech Scholar(CSE) M.Tech Scholar(CSE) Assistant Professor, Dept of CSE
Sri Indu College of Engg and Tech Sri Indu College of Engg and Tech Sri Indu College of Engg and Tech
Ibrahimpatan, Hyderabad, TS, India Ibrahimpatan, Hyderabad, TS, India Ibrahimpatan, Hyderabad, TS, India
Abstract: This paper builds an algorithm for sharing simple integer data on top of secure sum data mining operation using Newton’s identities and Sturm’s theorem. Algorithm for anonymous sharing of private data among parties is developed. This assignment is anonymous in that the identities received are unknown to the other members of the group. Resistance to collusion among other members is verified in an information theoretic sense when private communication channels are used. This assignment of serial numbers allows more complex data to be shared and has applications to other problems in privacy preserving data mining, collision avoidance in communications and distributed database access. The new algorithms are built on top of a secure sum data mining operation using Newton’s identities and Sturm’s theorem. An algorithm for distributed solution of certain polynomials over finite fields enhances the scalability of the algorithms.
Key words: Cloud, Website, information sharing, DBMS, ID, ODBC, ASP.NET
.
Privacy Preservation And Data Security In Location Based ServicesEditorJST
This document summarizes a research paper about preserving privacy and security in location-based services. It proposes a two-stage approach using oblivious transfer and a data retrieval phase to allow a user to query a database without revealing their identity or location to the server. The data on the server is encrypted for security. An intermediate service provider acts as a trusted third party to facilitate the private queries. If data is attacked, it can be recovered from a secondary server using message authentication codes to detect changes. The goal is to let users access location data privately while also protecting the server's data.
Modeling and Detection of Data Leakage FraudIOSR Journals
This document proposes strategies for detecting data leakage when sensitive data is distributed through trusted agents. It aims to detect leakage without modifying the original data objects. The key strategies are to personalize data objects for each agent by mixing in fake objects that contain the agent's identity. When objects are leaked, the distributor can use the fake objects to detect leakage and identify the guilty agent. The strategies were tested with a prototype application and showed to be effective for real-time leakage detection and agent identification without changing the original data objects.
The document describes a privacy-preserving method for detecting inadvertent leaks of sensitive data in network traffic. The method allows an organization to outsource detection to a provider without revealing the actual sensitive data. It involves the organization computing digests of the sensitive data and sharing a sample with the provider. The provider searches traffic for matches and returns potential leaks. The organization then determines if any are true leaks, protecting the privacy of the sensitive data from the provider. The method was implemented and evaluated on real datasets, showing accurate detection while preserving privacy.
GDPR BigDataRevealed Readiness Requirements and EvaluationSteven Meister
This GDPR methodology can evaluate your GDPR readiness. For those feeling GDPR ready, you may uncover complex issues often neglected. For those that have waited, you can gain knowledge providing for a more successful GDPR outcome.
https://youtu.be/uE4Q7u0LatU https://youtu.be/R37S9mIiVAk https://youtu.be/AQf3if7DnuM
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
Interplay of Digital Forensics in eDiscoveryCSCJournals
Digital forensics is often confused with eDiscovery (electronic discovery). However, both the fields are highly independent of the other but slightly overlap to assist each other in a symbiotic relationship. With decreasing costs of cloud storage, growing Internet speeds, and growing capacity of portable storage media, their chances of being used in a crime have grown. Sifting through large volumes of evidential data during eDiscovery or forensically investigating them requires teams from both these fields to work together on a case. In this paper, the authors discuss the relationship between these disciplines and highlight the digital forensic skills required, sub-disciplines of digital forensics, the possible electronic artifacts that can be encountered in a case, and the forensic opportunities relative to the eDiscovery industry. Lastly, the authors touch upon the best practices in digital evidence management during the eDiscovery process.
The Constrained Method of Accessibility and Privacy Preserving Of Relational ...IJERA Editor
Now in organizations or companies maximum information or data available and that data are related to tabular
form means relational database. Sometimes organization wanted to distribute that particular information or data
in within organization or other organization in daily basis. Here the thing is that the organization faces the some
kind of problems of security related because they distributed that information for its purposes and here
sometimes organization wanted that particular information will be modified or upgraded, Now they can used
numbers of methods or technics for encryption and electronic signatures for given a security and protection of
that particular data in during transmission network. In that protection of that protection used various different
mechanisms and strong methods for accessing that specific that particular data or information. It is very well
known that current or today the proper data must take as access control polices. Also some kind of methods for
CIA towards database system must be adopted
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
Automated hierarchical classification of scanned documents using convolutiona...IJECEIAES
This research proposed automated hierarchical classification of scanned documents with characteristics content that have unstructured text and special patterns (specific and short strings) using convolutional neural network (CNN) and regular expression method (REM). The research data using digital correspondence documents with format PDF images from Pusat Data Teknologi dan Informasi (Technology and Information Data Center). The document hierarchy covers type of letter, type of manuscript letter, origin of letter and subject of letter. The research method consists of preprocessing, classification, and storage to database. Preprocessing covers extraction using Tesseract optical character recognition (OCR) and formation of word document vector with Word2Vec. Hierarchical classification uses CNN to classify 5 types of letters and regular expression to classify 4 types of manuscript letter, 15 origins of letter and 25 subjects of letter. The classified documents are stored in the Hive database in Hadoop big data architecture. The amount of data used is 5200 documents, consisting of 4000 for training, 1000 for testing and 200 for classification prediction documents. The trial result of 200 new documents is 188 documents correctly classified and 12 documents incorrectly classified. The accuracy of automated hierarchical classification is 94%. Next, the search of classified scanned documents based on content can be developed.
Achieving Privacy in Publishing Search logsIOSR Journals
The document discusses algorithms for publishing search logs while preserving user privacy. It analyzes a search log using an algorithm that produces three types of outputs: query counts, a query-action graph showing query-result click counts, and a query-reformulation graph showing query suggestions clicked. The algorithm adds noise to query counts before publishing to achieve differential privacy. It aims to provide useful aggregated information for applications like search improvement while preventing re-identification of individual user data in the search log.
This document summarizes a research article that proposes using a convolutional neural network (CNN) to detect malware in PDF files. The researchers collected benign and malicious PDF files, extracted byte sequences, and manually labeled the data. They designed a CNN model to interpret patterns in the byte sequence data and predict whether a file contains malware. Their experimental results showed that the proposed CNN model outperformed other machine learning models in malware detection of PDF files.
FUZZY FINGERPRINT METHOD FOR DETECTION OF SENSITIVE DATA EXPOSUREIJCI JOURNAL
Protecting confidential information is a major concern for organizations and individuals alike, who stand
to suffer huge losses if private data falls into the wrong hands. Network-based information leaks pose a
serious threat to confidentiality. This paper describes network-based data-leak detection (DLD) technique,
the main feature of which is that the detection does not require the data owner to reveal the content of the
sensitive data. Instead, only a small amount of specialized digests are needed. The technique referred to as
the fuzzy fingerprint – can be used to detect accidental data leaks due to human errors or application flaws.
The privacy-preserving feature of algorithms minimizes the exposure of sensitive data and enables the data
owner to safely delegate the detection to others
Psdot 13 robust data leakage and email filtering systemZTech Proje
FINAL YEAR IEEE PROJECTS,
EMBEDDED SYSTEMS PROJECTS,
ENGINEERING PROJECTS,
MCA PROJECTS,
ROBOTICS PROJECTS,
ARM PIC BASED PROJECTS, MICRO CONTROLLER PROJECTS Z Technologies, Chennai
This document provides an overview of the ELISE smart search and matching solution. It can be used for employment matching to help job seekers find suitable jobs and employers find qualified candidates. It replicates data from other databases and uses techniques like semantic search, fuzzy matching, and proximity matching to return relevant results. The solution is designed to handle large volumes of structured and unstructured data across multiple languages and supports integration with other systems through APIs.
Collusion Attack: A Kernel-Based Privacy Preserving Techniques in Data Miningdbpublications
Data leakage happens whenever a system that is designed to be closed to an eavesdropper reveals some information to unauthorized parties. We know that for business purpose, it is necessary to transfer important data among many business partner and between the numbers of employees. But during this transfer of data, information is reach to unauthorized person. So it is very challenging and necessary to find leakage and guilty person responsible for information leakage. In this system we find the person which is responsible for the leakage of text as well as image file. For this we used distributor and agent. Distributor means owner of data and agents means trusted parties to whom we send data. This system finds the insider collusion attack. An insider attack is a malicious threat to an organization that come from people within the organization such as employees, contractor or business associate, who have inside information concerning the organization’s security practices, data and computer system. The main aim of this system is to find data of owner which is leaked and detect agent who leaked data. Here for text data we used kernel based algorithm and for image file we used steganography concept.
LocX is a system that provides location privacy in geo-social applications without adding uncertainty to location data or relying on assumptions about server security. It applies secure, user-specific coordinate transformations to location data before sharing with servers. Friends share the same transformation secrets, allowing location queries to be correctly evaluated by servers, while preventing servers from seeing actual location data. LocX guarantees privacy even against powerful adversaries, and prototypes show it provides privacy with little performance overhead for mobile devices.
This document reviews securing cloud data using fog computing. It proposes using user behavior profiling and decoy technology to detect unauthorized access to cloud data. User behavior profiling models normal patterns of how, when and how much a user accesses cloud data. Deviations from this baseline may signal a masquerade attack. Decoy information like fake documents are generated and can be returned to attackers, confusing them into thinking they have accessed real data when they have not. The document discusses these techniques and compares them to related work on using software decoys and addressing security and legal issues in cloud computing.
Privacy preserving optimal meeting location determination on mobile devicesAdz91 Digital Ads Pvt Ltd
The document proposes privacy-preserving algorithms for determining an optimal meeting location for a group of users. It aims to solve this fair rendezvous point (FRVP) problem in a way that protects users' location privacy from both other users and third-party service providers. The algorithms utilize homomorphic encryption to privately compute the meeting point from users' location preferences without revealing those preferences. The document evaluates the privacy and performance of the algorithms through both theoretical analysis and prototype implementation on mobile devices.
This document proposes a scheme to enhance security in cloud computing. It discusses how a user's data stored with a cloud provider could be at risk if the provider's internal staff can access the encrypted data. The proposed scheme aims to avoid unauthorized access of user data by sending a message to the user's mobile number when a transaction starts. It also displays fake information if login is unsuccessful to avoid further intrusion attempts. Common security methods for user data protection include encryption before storage, user authentication, and secure transmission channels. Cloud computing provides on-demand access to computing resources over the Internet and allows users to access services without knowledge of the infrastructure.
A study of index poisoning in peer topeerIJCI JOURNAL
P2P file sharing systems are the most popular forms of file sharing to date. Its client-server architecture
attains faster file transfers, however with its peer anonymity and lack of authentication it has become a
gold mine for malicious attacks. One of the leading sources of disruptions in the P2P file sharing systems is
the index poisoning attacks. This attack seeks to corrupt the indexes used to reference files available for
download in P2P systems with false data. In order to protect the users from these attacks it is important to
find solutions to eliminate or mitigate the effects of index poisoning attacks. This paper will analyze index
poisoning attacks, their uses and solutions proposed to defend against them.
Privacy - Preserving Reputation with Content Protecting Location Based Queriesiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Multilevel Privacy Preserving by Linear and Non Linear Data DistortionIOSR Journals
This document discusses privacy-preserving techniques for data mining called multilevel privacy preserving. It introduces the concept of generating multiple perturbed copies of data at different trust levels to protect privacy while allowing useful data mining. Key techniques discussed include data perturbation through adding random noise or distorting values, as well as data modification through aggregation, suppression, and swapping. Maintaining privacy is achieved by ensuring the noise added to different copies has a "corner-wave" covariance structure so statistical values do not differ significantly from the original data.
Cost-Effective Authentic and Anonymous Data Sharing with Forward Security1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
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2. BCA/B.E(C.S)
3. B.Tech IT
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9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
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Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Increasing Security Level in Data Sharing Using Ring Signature in Cloud Envir...IJERA Editor
Sharing of Information in a cloud environment is inevitable in onward of cloud computing environment.
Security in accessing cloud information has to consider many issues such as authentication, cost, time in
uploading and many other criteria. Authentication of data is must for utilizing the others data and uploading our
own data has become tedious. Getting Certificate and for every access is long process and cost increases. Ring
signature gives an assurance to the user to build an unidentified and accurate information sharing system. It
allows a data individualistic to innominate authenticate his data which can be put into the cloud for storage or
analysis purpose. In Identity-Based (ID Based ) Ring Signature Members of this cluster can easily share data
avoiding the pricey certificate verification as done in the usual procedure. Forward Security re authentication
overhead is avoided in Ring Signature by using RSA Algorithm we further provide increased level of security in
reduced time, efficient and simple manner.
Dokumen tersebut membahas tentang prospek UKM di era perdagangan bebas dan globalisasi, mencakup tantangan seperti persaingan dari produk impor serta kebutuhan akan meningkatkan kualitas SDM dan daya saing. Kualitas SDM diidentifikasi sebagai faktor penting bagi keberhasilan UKM dalam menghadapi tantangan tersebut.
The Constrained Method of Accessibility and Privacy Preserving Of Relational ...IJERA Editor
Now in organizations or companies maximum information or data available and that data are related to tabular
form means relational database. Sometimes organization wanted to distribute that particular information or data
in within organization or other organization in daily basis. Here the thing is that the organization faces the some
kind of problems of security related because they distributed that information for its purposes and here
sometimes organization wanted that particular information will be modified or upgraded, Now they can used
numbers of methods or technics for encryption and electronic signatures for given a security and protection of
that particular data in during transmission network. In that protection of that protection used various different
mechanisms and strong methods for accessing that specific that particular data or information. It is very well
known that current or today the proper data must take as access control polices. Also some kind of methods for
CIA towards database system must be adopted
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
Automated hierarchical classification of scanned documents using convolutiona...IJECEIAES
This research proposed automated hierarchical classification of scanned documents with characteristics content that have unstructured text and special patterns (specific and short strings) using convolutional neural network (CNN) and regular expression method (REM). The research data using digital correspondence documents with format PDF images from Pusat Data Teknologi dan Informasi (Technology and Information Data Center). The document hierarchy covers type of letter, type of manuscript letter, origin of letter and subject of letter. The research method consists of preprocessing, classification, and storage to database. Preprocessing covers extraction using Tesseract optical character recognition (OCR) and formation of word document vector with Word2Vec. Hierarchical classification uses CNN to classify 5 types of letters and regular expression to classify 4 types of manuscript letter, 15 origins of letter and 25 subjects of letter. The classified documents are stored in the Hive database in Hadoop big data architecture. The amount of data used is 5200 documents, consisting of 4000 for training, 1000 for testing and 200 for classification prediction documents. The trial result of 200 new documents is 188 documents correctly classified and 12 documents incorrectly classified. The accuracy of automated hierarchical classification is 94%. Next, the search of classified scanned documents based on content can be developed.
Achieving Privacy in Publishing Search logsIOSR Journals
The document discusses algorithms for publishing search logs while preserving user privacy. It analyzes a search log using an algorithm that produces three types of outputs: query counts, a query-action graph showing query-result click counts, and a query-reformulation graph showing query suggestions clicked. The algorithm adds noise to query counts before publishing to achieve differential privacy. It aims to provide useful aggregated information for applications like search improvement while preventing re-identification of individual user data in the search log.
This document summarizes a research article that proposes using a convolutional neural network (CNN) to detect malware in PDF files. The researchers collected benign and malicious PDF files, extracted byte sequences, and manually labeled the data. They designed a CNN model to interpret patterns in the byte sequence data and predict whether a file contains malware. Their experimental results showed that the proposed CNN model outperformed other machine learning models in malware detection of PDF files.
FUZZY FINGERPRINT METHOD FOR DETECTION OF SENSITIVE DATA EXPOSUREIJCI JOURNAL
Protecting confidential information is a major concern for organizations and individuals alike, who stand
to suffer huge losses if private data falls into the wrong hands. Network-based information leaks pose a
serious threat to confidentiality. This paper describes network-based data-leak detection (DLD) technique,
the main feature of which is that the detection does not require the data owner to reveal the content of the
sensitive data. Instead, only a small amount of specialized digests are needed. The technique referred to as
the fuzzy fingerprint – can be used to detect accidental data leaks due to human errors or application flaws.
The privacy-preserving feature of algorithms minimizes the exposure of sensitive data and enables the data
owner to safely delegate the detection to others
Psdot 13 robust data leakage and email filtering systemZTech Proje
FINAL YEAR IEEE PROJECTS,
EMBEDDED SYSTEMS PROJECTS,
ENGINEERING PROJECTS,
MCA PROJECTS,
ROBOTICS PROJECTS,
ARM PIC BASED PROJECTS, MICRO CONTROLLER PROJECTS Z Technologies, Chennai
This document provides an overview of the ELISE smart search and matching solution. It can be used for employment matching to help job seekers find suitable jobs and employers find qualified candidates. It replicates data from other databases and uses techniques like semantic search, fuzzy matching, and proximity matching to return relevant results. The solution is designed to handle large volumes of structured and unstructured data across multiple languages and supports integration with other systems through APIs.
Collusion Attack: A Kernel-Based Privacy Preserving Techniques in Data Miningdbpublications
Data leakage happens whenever a system that is designed to be closed to an eavesdropper reveals some information to unauthorized parties. We know that for business purpose, it is necessary to transfer important data among many business partner and between the numbers of employees. But during this transfer of data, information is reach to unauthorized person. So it is very challenging and necessary to find leakage and guilty person responsible for information leakage. In this system we find the person which is responsible for the leakage of text as well as image file. For this we used distributor and agent. Distributor means owner of data and agents means trusted parties to whom we send data. This system finds the insider collusion attack. An insider attack is a malicious threat to an organization that come from people within the organization such as employees, contractor or business associate, who have inside information concerning the organization’s security practices, data and computer system. The main aim of this system is to find data of owner which is leaked and detect agent who leaked data. Here for text data we used kernel based algorithm and for image file we used steganography concept.
LocX is a system that provides location privacy in geo-social applications without adding uncertainty to location data or relying on assumptions about server security. It applies secure, user-specific coordinate transformations to location data before sharing with servers. Friends share the same transformation secrets, allowing location queries to be correctly evaluated by servers, while preventing servers from seeing actual location data. LocX guarantees privacy even against powerful adversaries, and prototypes show it provides privacy with little performance overhead for mobile devices.
This document reviews securing cloud data using fog computing. It proposes using user behavior profiling and decoy technology to detect unauthorized access to cloud data. User behavior profiling models normal patterns of how, when and how much a user accesses cloud data. Deviations from this baseline may signal a masquerade attack. Decoy information like fake documents are generated and can be returned to attackers, confusing them into thinking they have accessed real data when they have not. The document discusses these techniques and compares them to related work on using software decoys and addressing security and legal issues in cloud computing.
Privacy preserving optimal meeting location determination on mobile devicesAdz91 Digital Ads Pvt Ltd
The document proposes privacy-preserving algorithms for determining an optimal meeting location for a group of users. It aims to solve this fair rendezvous point (FRVP) problem in a way that protects users' location privacy from both other users and third-party service providers. The algorithms utilize homomorphic encryption to privately compute the meeting point from users' location preferences without revealing those preferences. The document evaluates the privacy and performance of the algorithms through both theoretical analysis and prototype implementation on mobile devices.
This document proposes a scheme to enhance security in cloud computing. It discusses how a user's data stored with a cloud provider could be at risk if the provider's internal staff can access the encrypted data. The proposed scheme aims to avoid unauthorized access of user data by sending a message to the user's mobile number when a transaction starts. It also displays fake information if login is unsuccessful to avoid further intrusion attempts. Common security methods for user data protection include encryption before storage, user authentication, and secure transmission channels. Cloud computing provides on-demand access to computing resources over the Internet and allows users to access services without knowledge of the infrastructure.
A study of index poisoning in peer topeerIJCI JOURNAL
P2P file sharing systems are the most popular forms of file sharing to date. Its client-server architecture
attains faster file transfers, however with its peer anonymity and lack of authentication it has become a
gold mine for malicious attacks. One of the leading sources of disruptions in the P2P file sharing systems is
the index poisoning attacks. This attack seeks to corrupt the indexes used to reference files available for
download in P2P systems with false data. In order to protect the users from these attacks it is important to
find solutions to eliminate or mitigate the effects of index poisoning attacks. This paper will analyze index
poisoning attacks, their uses and solutions proposed to defend against them.
Privacy - Preserving Reputation with Content Protecting Location Based Queriesiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Multilevel Privacy Preserving by Linear and Non Linear Data DistortionIOSR Journals
This document discusses privacy-preserving techniques for data mining called multilevel privacy preserving. It introduces the concept of generating multiple perturbed copies of data at different trust levels to protect privacy while allowing useful data mining. Key techniques discussed include data perturbation through adding random noise or distorting values, as well as data modification through aggregation, suppression, and swapping. Maintaining privacy is achieved by ensuring the noise added to different copies has a "corner-wave" covariance structure so statistical values do not differ significantly from the original data.
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Increasing Security Level in Data Sharing Using Ring Signature in Cloud Envir...IJERA Editor
Sharing of Information in a cloud environment is inevitable in onward of cloud computing environment.
Security in accessing cloud information has to consider many issues such as authentication, cost, time in
uploading and many other criteria. Authentication of data is must for utilizing the others data and uploading our
own data has become tedious. Getting Certificate and for every access is long process and cost increases. Ring
signature gives an assurance to the user to build an unidentified and accurate information sharing system. It
allows a data individualistic to innominate authenticate his data which can be put into the cloud for storage or
analysis purpose. In Identity-Based (ID Based ) Ring Signature Members of this cluster can easily share data
avoiding the pricey certificate verification as done in the usual procedure. Forward Security re authentication
overhead is avoided in Ring Signature by using RSA Algorithm we further provide increased level of security in
reduced time, efficient and simple manner.
Dokumen tersebut membahas tentang prospek UKM di era perdagangan bebas dan globalisasi, mencakup tantangan seperti persaingan dari produk impor serta kebutuhan akan meningkatkan kualitas SDM dan daya saing. Kualitas SDM diidentifikasi sebagai faktor penting bagi keberhasilan UKM dalam menghadapi tantangan tersebut.
10 Hábitos Saludables para Emprendedores para vivir al máximoEmmanuel Gutierrez
10 Hábitos Saludables para Emprendedores para vivir al máximo
Consejos para desarrollar una actitud optima para enfrentar los retos de nuestros proyectos.
http://emmanuelgutierrez.com/habitos-saludables-para-emprendedores/
Este documento propõe três recomendações ao governo para melhorar a situação dos professores contratados: 1) alterar as regras de vinculação de acordo com a diretiva europeia sobre contratos a termo, 2) considerar o limite de três contratos sucessivos permitido pelo código do trabalho, 3) criar um mecanismo extraordinário para vincular professores vítimas das regras atuais que tiveram contratos sucessivos por vários anos.
This document provides information about purchasing a 3Com 3CR17661 switch from Launch 3 Telecom. It describes payment and shipping options, same-day shipping availability, warranty and return policies, and additional services offered like repairs, maintenance contracts, de-installation, and recycling. Customers can purchase the switch by phone, email, or online request form and receive order confirmation and tracking information.
Maria Guadalupe Montemayor De la Garza has over 20 years of experience in customer service, materials management, and human resources roles for automotive suppliers. She has worked for Summit Plastics, Magna Decofimex, Autoliv, and other companies supporting Ford, GM, Chrysler, and other automakers. Currently she is the Materials Supervisor at Summit Plastics in Silao, Mexico where she manages customer releases, production planning, inventory, and shipping.
El documento discute cómo las tecnologías de la información y la comunicación (TIC) pueden apoyar el proceso de enseñanza y aprendizaje. Explica que la integración de las TIC en la docencia debe ser un proceso gradual guiado por objetivos pedagógicos y con apoyo institucional. También destaca los desafíos de la integración de las TIC como la sobrecarga de trabajo y comunicación, y la falta de motivación y apoyo técnico y pedagógico.
Este documento describe los componentes principales de una tarjeta madre, incluyendo el procesador, memoria RAM, ranuras de expansión, chipset y otros. Explica los tipos comunes de tarjetas madres como ATX y AT, e identifica componentes como el BIOS, buses y conectores. También proporciona instrucciones para limpiar una tarjeta madre retirando el polvo de ventiladores, ranuras y otros componentes.
This document provides information about purchasing a 3Com 1698510051101 product from Launch 3 Telecom. It describes the product, payment and shipping options, warranty, and additional services offered by Launch 3 Telecom such as repairs, maintenance contracts, de-installation, and telecom equipment recycling. Customers can purchase the product by phone, email, or online request form and receive same day shipping with tracking if ordered before 3pm.
Jan Lundius has extensive experience working for international organizations such as UNESCO, FAO, WFP, IFAD, and UNDP. He has a PhD in History of Religions from Lund University in Sweden. His work has involved gender mainstreaming, indigenous peoples issues, rural development, and project evaluation in Latin America, Africa, Asia, and the Middle East. He is fluent in Swedish, English, and Spanish and has a good working knowledge of several other languages.
Dean Burgess is seeking a career change into teaching after having a background in leadership, management, and training. He has a master's degree in English and creative writing as well as a bachelor's degree in human resources management. Burgess has over 15 years of work experience in roles such as department manager, warehouse manager, security, and shift manager. He wants to become an educator to positively influence students and find reward in their success.
Data Allocation Strategies for Leakage DetectionIOSR Journals
This document summarizes data allocation strategies for detecting data leakage when sensitive data is distributed through trusted agents. It proposes injecting "fake but genuine-looking" data along with real data to improve the ability to detect if leakage occurs and identify the agent responsible. Various allocation algorithms are presented, including random selection and maximizing the difference between agents' probabilities of guilt. Empirical results show the average detection metric is improved when fake data is used compared to no fake data. The strategies aim to detect leakage without modifying the original data, unlike traditional watermarking techniques.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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.
Misusability Measure Based Sanitization of Big Data for Privacy Preserving Ma...IJECEIAES
Leakage and misuse of sensitive data is a challenging problem to enterprises. It has become more serious problem with the advent of cloud and big data. The rationale behind this is the increase in outsourcing of data to public cloud and publishing data for wider visibility. Therefore Privacy Preserving Data Publishing (PPDP), Privacy Preserving Data Mining (PPDM) and Privacy Preserving Distributed Data Mining (PPDM) are crucial in the contemporary era. PPDP and PPDM can protect privacy at data and process levels respectively. Therefore, with big data privacy to data became indispensable due to the fact that data is stored and processed in semi-trusted environment. In this paper we proposed a comprehensive methodology for effective sanitization of data based on misusability measure for preserving privacy to get rid of data leakage and misuse. We followed a hybrid approach that caters to the needs of privacy preserving MapReduce programming. We proposed an algorithm known as Misusability Measure-Based Privacy Preserving Algorithm (MMPP) which considers level of misusability prior to choosing and application of appropriate sanitization on big data. Our empirical study with Amazon EC2 and EMR revealed that the proposed methodology is useful in realizing privacy preserving Map Reduce programming.
The document proposes a system called SecNet that uses blockchain and AI to securely store, compute, and share data at scale on the internet. It aims to enable real big data and powerful AI by:
1) Using blockchain to allow trusted data sharing while guaranteeing data ownership.
2) Developing an AI-based secure computing platform to intelligently generate security rules and construct a trusted cyberspace.
3) Establishing a value-exchange mechanism where participants are rewarded for providing data or services, promoting more data sharing and better AI performance.
The system is described as a way to address current issues where data is scattered and controlled by different stakeholders without trust, and complex data usage is difficult to
Performance Analysis of Hybrid Approach for Privacy Preserving in Data Miningidescitation
Now-a day’s data sharing between two organizations
is common in many application areas like business planning
or marketing. When data are to be shared between parties,
there could be some sensitive data which should not be
disclosed to the other parties. Also medical records are more
sensitive so, privacy protection is taken more seriously. As
required by the Health Insurance Portability and
Accountability Act (HIPAA), it is necessary to protect the
privacy of patients and ensure the security of the medical
data. To address this problem, released datasets must be
modified unavoidably. We propose a method called Hybrid
approach for privacy preserving and implemented it. First we
randomized the original data. Then we have applied
generalization on randomized or modified data. This
technique protect private data with better accuracy, also it can
reconstruct original data and provide data with no information
loss, makes usability of data.
Cluster Based Access Privilege Management Scheme for DatabasesEditor IJMTER
Knowledge discovery is carried out using the data mining techniques. Association rule mining,
classification and clustering operations are carried out under data mining. Clustering method is used to group up the
records based on the relevancy. Distance or similarity measures are used to estimate the transaction relationship.
Census data and medical data are referred as micro data. Data publish schemes are used to provide private data for
analysis. Privacy preservation is used to protect private data values. Anonymity is considered in the privacy
preservation process.
Data values are allowed to authorized users using the access control models. Privacy Protection Mechanism
(PPM) uses suppression and generalization of relational data to anonymize and satisfy privacy needs. Accuracyconstrained privacy-preserving access control framework is used to manage access control in relational database. The
access control policies define selection predicates available to roles while the privacy requirement is to satisfy the kanonymity or l-diversity. Imprecision bound constraint is assigned for each selection predicate. k-anonymous
Partitioning with Imprecision Bounds (k-PIB) is used to estimate accuracy and privacy constraints. Role-based Access
Control (RBAC) allows defining permissions on objects based on roles in an organization. Top Down Selection
Mondrian (TDSM) algorithm is used for query workload-based anonymization. The Top Down Selection Mondrian
(TDSM) algorithm is constructed using greedy heuristics and kd-tree model. Query cuts are selected with minimum
bounds in Top-Down Heuristic 1 algorithm (TDH1). The query bounds are updated as the partitions are added to the
output in Top-Down Heuristic 2 algorithm (TDH2). The cost of reduced precision in the query results is used in TopDown Heuristic 3 algorithm (TDH3). Repartitioning algorithm is used to reduce the total imprecision for the queries.
The privacy preserved access privilege management scheme is enhanced to provide incremental mining
features. Data insert, delete and update operations are connected with the partition management mechanism. Cell level
access control is provided with differential privacy method. Dynamic role management model is integrated with the
access control policy mechanism for query predicates.
Data leakage detbxhbbhhbsbssusbgsgsbshsbsection.pdfnaresh2004s
This document discusses data leakage detection techniques. It begins with an introduction to data leakage and examples of how it occurs when data is shared with third parties. It then summarizes some of the largest data breaches of the 21st century. Existing data leakage detection techniques like watermarking and steganography are described along with their disadvantages. The document discusses future applications and scope in the area of data leakage detection and concludes that such techniques can help identify sources of data leaks while data is distributed.
This document discusses data leakage detection techniques. It begins with an introduction to data leakage and examples of how it occurs when data is shared with third parties. It then summarizes some of the largest data breaches of the 21st century involving Yahoo, eBay, Uber and Election Systems & Software. Existing detection techniques like watermarking and steganography are explained along with their drawbacks. Applications of detection include identifying who leaked the data to reduce cybercrime. Future work aims to model agent guilt and handle online data allocation to agents.
Introduction, How data leakage takes place, Biggest data breaches of the 21st century, Existing data leakage detection techniques, Disadvantages of existing techniques, Future scope of Data Leakage Detection ,Applications, Conclusion
Protecting the private data from publishing has
become a requisite in today's world of data. This solves the
problem of divulging the sensitive data when it is mined.
Amongst the prevailing privacy models, ϵ-differential privacy
outfits one of the strongest privacy guarantees. In this paper,
we address the problem of private data publishing on vertically
partitioned data, where different attributes exist for same set of
individuals. This operation is simulated between two parties. In
specific, we present an algorithm with differentially private
data release for vertically partitioned data between two parties
in the semi-honest adversary model. First step towards
achieving this is to present a two party protocol for exponential
mechanism. By the same token, a two-party algorithm that
releases differentially private data in a secure way following
secure multiparty computation is implemented. A set of
investigational results on the real-life data indicate that the
proposed algorithm can effectively safeguard the information
for a data mining task.
This document proposes a scalable two-phase top-down specialization (TDS) approach to anonymize large-scale datasets using MapReduce on cloud computing. It addresses the challenges of handling large datasets and achieving privacy preservation when the data is stored in a cloud application. The approach uses two phases: 1) data partitioning to cluster the large dataset, and 2) anonymization level merging to combine the clustered tasks into a large-scale anonymized dataset. By combining the two-phase TDS approach with MapReduce, it aims to anonymize data in a highly scalable way while maintaining privacy.
Cloud assisted mobile-access of health data with privacy and auditabilityShakas Technologies
The document proposes a cloud-assisted mobile health system that allows patients to securely store and search health records in the cloud while preserving privacy. It discusses existing privacy issues with electronic health systems and proposes a system using private cloud services, searchable symmetric encryption, identity-based encryption and attribute-based encryption to ensure data confidentiality, anonymity, unlinkability, and auditability of data access. The system is designed to store encrypted health records on the cloud and allow authorized users like doctors to securely search and access records when needed, including in emergency situations.
Information Leakage Prevention Using Public Key Encryption System and Fingerp...CSCJournals
This document proposes and evaluates a system using RSA public key encryption, fingerprint authentication, and the Apriori algorithm to prevent information leakage. The system generates encryption keys for users based on registration details including fingerprints. Users encrypt messages with the public key before sending. The administrator verifies identities using fingerprints matched with the Apriori algorithm before decrypting messages with the private key. The system was tested on a university network and achieved high security preventing unauthorized access to data.
The document discusses data leakage detection. It introduces data leakage detection and describes why data mining is used. It defines key terms like data leakage and data privacy. It then describes the existing system that can detect hackers but with limited evidence, and the proposed system that can better trace hackers with more evidence. It also lists the types of employees that may leak data, such as the security illiterate, gadget nerds, unlawful residents, and malicious employees. Finally, it provides an example figure of data leakage.
In recent days Cloud computing is a rising technique
which offers data sharing with more efficient, effective and
economical approaches between group members. To create an
authentic and anonymous data sharing, IDentity based Ring
Signature (ID-RS) is one of the promising technique between
the groups. Ring signature scheme permits the manager or data
owner to authenticate into the system in anonymous manner.
In conventional Public Key Infrastructure (PKI) data sharing
scheme contains certificate authentication process, which is a
bottleneck because of its high cost. To avoid this problem, we
proposed Cost Optimized Identity based Ring Signature with
forward secrecy (COIRS) scheme. This scheme helps to remove
the traditional certificate verification process. Only once the user
needs to be verified by the manager giving his public details. The
cost and time required for this process is comparatively less than
traditional public key infrastructure. If the secret key holder has
been compromised, all early generated signatures remains valid
(Forward Secrecy). This paper discuss about how to optimize the
time and cost when sharing the files to the cloud. We provide a
protection from collision attack, which means revoked users will
not get the original documents. In general better efficiency and
secrecy can be provided for group sharing by applying above
approaches.
Enabling Use of Dynamic Anonymization for Enhanced Security in CloudIOSR Journals
This document summarizes various techniques for anonymizing data to protect privacy and security when data is stored in the cloud. It discusses how anonymization removes identifying attributes from data to prevent individuals from being identified. The document reviews existing anonymization models like k-anonymity, l-diversity and t-closeness. It then describes different anonymization techniques like hashing, hiding, permutation, shifting, truncation, prefix-preserving and enumeration that were implemented to anonymize data fields. The goal is to anonymize data in a way that balances privacy, security, and the ability to still use the data for appropriate purposes.
Cost effective authentic and anonymous data sharing with forward securityPvrtechnologies Nellore
This document proposes a system for anonymous and authentic data sharing on a large scale using identity-based ring signatures with forward security. It aims to address issues of efficiency, data integrity, and privacy for data owners. The system would allow data owners to anonymously authenticate their data, which could then be stored and analyzed on the cloud. Identity-based ring signatures eliminate the need for certificate verification, improving efficiency. Forward security is added so that if a user's secret key is compromised, previously generated signatures including that user remain valid. This is important for large-scale data sharing systems to avoid needing to reauthenticate all data if a single key is compromised. The document outlines the modules of the proposed system and describes identity-based ring signatures
Secure system based on recombined fingerprints for sharing multimedia files i...eSAT Journals
Abstract In this paper the execution time is less when compared to previous algorithm. And also it provide security between the merchant and buyer The traitor tracing protocol is used to detect the illegal transaction. Here we used fingerprinting solution to avoid illegal redistribution of multimedia contents. Here we convert the multimedia video file into image then encrypting the image after the encrypted image will be transferred from merchant to buyer. The buyer receives the copyright protection from merchant, he decrypts the image then converts it into video. After that, the copyright protection of file is transferred to child buyer. Then tracing traitor protocol is used to checks the fingerprints for merchant to buyer and buyer to child buyer. Traitor tracing protocol is used to detect the illegal transaction of the content. The Blowfish algorithm is used to encrypt and decrypt the multimedia files. Finally we detect the performance of our work based on efficiency, accuracy and we achieve security. Keywords: Fingerprint, Multimedia files, Blowfish algorithm, Merchant, Buyer, Child Buyer, Copyright Protection
Secure system based on recombined fingerprints for sharing multimedia files i...
AIDA ICITET
1. 1
Security And Privacy Preserving Data Sharing
Using Anonymous Identity Assignment(AIDA)
B Tulasi1
, N Pavithra Sahari2
, M Geetha3
, O. Pandithurai4
1,2 – UG, Department Of Computer Science and Engineering, Rajalakshmi Institute Of Technology
3,4 – Asst.Prof, Department Of Computer Science and Engineering, Rajalakshmi Institute Of Technology
Mail id: tulasirit@gmail.com1
, pavithrasahari@gmail.com2
, geethapandian@yahoo.com3
, pandics@gmail.com4
Abstract-It is very important that the people be able to
exercise control over how their personal data is
distributed, shared and sold. The control of information
remains in the hands of the owner of that information.
Hence, there is a necessity to maintain the privacy and
security of shared data communication across many
entities in the distributed system. Anonymity which is
used in the multiparty security, allows multiple parties
on a network in collaboration carry out a global
computation. The computations depend on data from
each party while the data held by each party remains
unknown to other parties. Existing and new algorithms
are examined for assigning anonymous IDs to the nodes
of the network where the IDs are anonymous using a
distributed computation. These IDs which are created
when the user is registered are considered as dummy
IDs.
Keywords -Anonymity,multiparty security,distributed
computation.
I. INTRODUCTION
Encryption, or the art of concealing information,
dates back thousands of years. Encryption only hides
what is being said. It does not hide who is talking to
whom. This information by itself can be used to one's
advantage or disadvantage. Anonymity as used in the
multiparty security, allows multiple parties on a
network to jointly carry out a global computation.
The computations depend on data from each party
while the data held by each party remains unknown
to other parties. The application can use either private
or public anonymous proxy servers, encryption or
even spoofing to ensure an anonymous and/or
difficultly traceable access to a resource. Most
commentary on the Internet is essentially done
anonymously, using unidentifiable false user names.
While these usernames can take on an identity of
their own, they are anonymous from the actual
author. Their distributed technology approach may
grant a higher degree of security than centralized
anonym zing services where a central point exists
that could disclose one's identity. It was shown that it
is possible to compromise the anonymity of many
Internet users by a group of collaborating
eavesdroppers even when the most central routers are
protected from eavesdropping. The relevance of
anonymity in various application domains: whistle
blowers, human rights work, health care, elections, e-
cash, political speech. Another form of anonymity,
Alice wants to talk to Bob without anyone, including
Bob, knowing her identity (sender anonymity). She
wants Bob to reply without anyone knowing her
identity (receiver anonymity). A network is
established across multiple heterogeneous users. Not
only the critical data but also their identities should
not be revealed to other members of the network. The
critical data is to be shared with maximum privacy
among trusted members when demanded.
The work reported in this paper further explores the
connection between sharing secrets in an anonymous
manner using distributed secure multiparty
computation and anonymous ID assignment. The use
of the term “anonymous” here differs from its
meaning in various research dealing with applications
such as leader election in anonymous networks.
Various networks are not anonymous and the
participants are identifiable in that they are known to
and can be addressed by the others. These IDs can be
used for sharing/dividing communication bandwidth,
data storage, and other resources without conflict.
The IDs are commonly needed in sensor networks for
security or for administrative tasks, such as
configuration and monitoring of individual nodes,
and download of binary code or data aggregation
descriptions to these nodes. An application where IDs
need to be anonymous is grid computing where one
may seek services without divulging the identity of
the service requestor.
II. RELAED WORK
Larry A. Dunning, et al [1] proposes a technique
which is used to assign the nodes ID numbers
iteratively. This assignment is anonymous where the
identities received are unknown to the other members
2. 2
of the group. The limitation of this technique is that
the heterogeneity is not achieved.
Q. Xie, et al [2]proposes that matchmaking is a key
component of mobile social networking where it
notifies users having shared interest and adds them to
theusers social network. The limitation is that this
approach reveals more personal information than
necessary.
A. Yao, et al [18] deals with secret voting such that
suppose a committee of m members wish to decide
on an yes-no action, each member is to write an
opinion. The results are obtained without knowing
the opinion of any other members. This paper
proposes private querying of database supposing
Alice wishes to compute a function f1 and is asking a
query from the database query system, then the query
is answered without knowing anything else about the
data in it. The limitation in this paper is that the
computation requires a larger number of
roundsinorder to serve anonymity.
J. Smith, et al [21]proposes that the distributed
protocol makes use of hardware random generation to
create unique ids. Random IDs of sufficient length
are independently chosen and does not require any
communication. The limitation is that computation
time is high.
J. Castellà-roca, et al [4] that e-gambling requires
standards of security similar to those in physical
gambling. Cryptographic tool have been commonly
used so far to provide security to e-gambling. They
offer the possibility of manipulating cards in
encrypted form.
III. MOTIVATING APPLICATIONS
We put forward two applications to make the above
paradigm concrete.
Application 1: Document Sharing
Enterprise R is shopping for technology and wishes
to find out if enterprise S has some intellectual
property it might want to license. However, R would
not like to reveal its complete data, nor would S like
to reveal all its unpublished data of intellectual
property. Rather, they would like to first, find the
specific technologies for which there is a match, and
then reveal information only about those
technologies. This problem can be abstracted as
follows. We have two databases DR and DS, where
each database contains a set of documents. The
document shave been preprocessed to only include
the most significant words, using some measure such
as term frequency times inverse document frequency.
We wish to find all pairs of similar documents dR 2
DR and dS 2 DS, without revealing the other
documents. In database terminology, we want to
compute the join of DR and DS using the join predi-
catef(jdR dSj;jdRj;jdSj) >, for some similarity
function f and threshold. The function f could be
jdRdSj=(jdRj+jdSj), for instance. Many applications
map to this abstraction. For example, two
government agencies may want to share documents,
but only on a need-to-know basis. They would like to
find similar documents contained in their repositories
in order to initiate their exchange.
Application 2: Medical Research
Imagine a future where many people have their DNA
sequenced. A medical researcher wants to validate a
supposition connecting a DNA sequence D with a
reaction to drugG. People who have taken the drug
are separated into four groups, based on whether they
had an adverse reaction and whether their DNA
contained the specific sequence; the researcher needs
the number of people in each group. DNA sequences
and medical records are stored in databases in
autonomous enterprises. Due to privacy concerns, the
enterprises do not wish to provide any information
about an individual’s DNA sequence or their medical
records, but still wish to help with the
research.Assume that the table TR(person id, pattern)
stores whether a person’s DNA contain patternD and
TS(person id, drug, reaction) checks whether a
person took drug G and whether the person had an
adverse reaction. TR and TS belong to two different
enterprises. The researcher should get to know the
counts and nothing else, and the enterprises should
not learn any new information about any individual.
IV. EXISTING SYSTEM
Here we discuss some existing techniques that is used
for building the above applications, and why they are
insufficient.
Trusted Third Party: The main parties give the data
to a “trusted” third party and have the third party do
the computation. However, the third party has to be
completely trusted with respect to competence
against security violation. The level of trust is
expected is to be too high for this solution to be
agreed.
Secure Multi-Party Computation: Given two
parties with inputs x and y respectively, the goal of
secure multi-party computation is to compute a
function f(x,y) such that the two parties learn only
f(x,y), and not x, y.
LIMITATIONS:
Schema discovery and Heterogeneity: We do not
address the question of how to find which database
contains which tables and what the attribute names
are. We assume that the database schemas are known
3. 3
and we also do not address the issues of
heterogeneity.
V. PROBLEM STATEMENT:
The problem we study in this paper is now formally
stated.
Problem Statement (Ideal): Let there be two parties
R (receiver) and S (sender) with databases DR and
DS respectively. Given a database query Q spanning
the tables in DR and DS, compute the answer to Q
and return it to R without revealing any additional
information to either party.
Problem Statement (Minimal Sharing): Let there
be two parties R and S with databases DR and DS
respectively. Given a database query Q spanning the
tables in DR and DS, and some categories of
information I, compute the answer to Q and return it
to R with- out revealing any additional information to
either party except for information contained in I. 2
For example, if the query Q is a join TR 1 TS over
two tables TR and TS, the additional information I
might be the number of records in each table: jTRj
and jTSj. Note that whatever R can infer from
knowing the answer to the query Q and the addi-
tional information I is fair game. For instance, if the
query Q is an intersection VS VR between two sets
VS and VR, then for all v 2 (VR (VS VR)), R knows
that these values were not in VS. We assume that the
query Q is revealed to both parties. One can think of
other applications where the format of Q is revealed,
but not the parameters of Q}
MINIMAL INFORMATION SHARING USING
SECURE SUM:
Efficient algorithms are developed for secure sum
data mining operation. It is a secure computation that
allows parties to compute the sum of their individual
inputs without disclosing the inputs to one another
and also helps characterize the complexities of the
secure multiparty computation. Let us consider a
group of hospitals with individual databases. The
hospitals compute and share only the average of a
data item, such as the number of hospital acquired
infections. The value of the data item is not revealed
to any member of the group. Thus N nodes n1,
n2,...nN have data items d1, d2,.... dN, and wish to
compute and share only the total value T = d1 + d2 +
.... dN.
SHARING COMPLEX DATA WITH AIDA:
The focus is to develop efficient algorithms on top of
a secure sum data mining operation. The identities
received are unknown to other members of the
network. Our algorithm is based on a method for
anonymously sharing simple data and results in
methods for efficient sharing of complex data.
Anonymous Identity Assignment (AIDA) is used for
assigning Identities to the nodes of a network. The
IDs are anonymous and required computations are
distributed using a central anonymous server. This
assignment is essentially a permutation of the
integers with each ID being known only to the node
to which it is assigned. Consider a situation where
parties wish to display their data collectively, but
anonymously on a third party site. The anonymous
IDs are used to assign the slots to users, while the
anonymous communication allows the parties to
conceal their identities from the third party.
Consider the possibility that more complex data is to
be shared amongst the participating nodes. Each node
has a data item of length b-bits which it wishes to
make public anonymously to the other participants.
As the number of bits per data item and the number
of nodes becomes larger, the methods performed in
the previous section becomes infeasible. Instead, to
establish this sharing, we will utilize an indexing of
the nodes. Methods for finding such an indexing are
developed in subsequent sections. Assume that each
node has a unique identification (ID) and no node has
knowledge of the ID number of any other node.
Find AIDA:
Given N nodes, use distributed computation to find
an anonymous indexing permutation.
1) Set the A = 0 [Initial number of assigned nodes].
2) Each unassigned node chooses a random number
in the range 1 to S. A node assigned in a previous
round chooses r = 0.
3) The shared values are denoted by q.
4) Consider k is the number of unique random values.
The index of the nodes is derived from the position of
their random number in the revised list after being
sorted:
4. 4
s = A + Card {q <= k}
5) Now, the number of nodes assigned A = A + k
6) If A < k then return to step (2).
Protocol for Secure Computations:
For definiteness, suppose Alice requests for the
current time to Bob considering the central server
anonymous. Now Alice is sending a query to the
database requesting for the current time. The request
is made anonymous using the anonymous server and
is sent Bob. Bob has no knowledge about Alice while
he can view only the query from the server (sender
anonymity). Using secure computations, Bob
responds to the server and the server then sends the
current time to Alice without revealing Bob's identity
(receiver anonymity).
VI. EXPERIMENT AND RESULTS
The proposed application is made available to a
variety of hospitals. In this system the patient’s
medical records are saved and the system keeps track
if these records. The information related to the
patients are stored anonymously in the database. To
achieve this, the health care management system's
information is stored and retrieved by preserving its
anonymity. Whenever the patient’s information is
entered, it is stored into the anonymous server and an
anonymous identity is created in the database. This
ID is unique and concealed. The doctor’s information
is also fed into the system in order to identify who
treated the patient in case of any emergency. During
the time of retrieval, only the patient’s information
can be viewed, whereas the anonymous identities
remain unknown.
VII. CONCLUSION
Each algorithm compared in the above sections can
be reasonably implemented and each has its own
advantages. With private communication channels,
our algorithms are secure in an information
hypothetic sense. The problem of mental poker is
also similar to our algorithm and has shown to have
no such solution with two players and three cards.
The argument of can easily be extended to, e.g., two
sets each of colluding players with a deck of cards
rather than our deck of cards. In contrast to bounds
on completion time developed in previous works, our
formulae give the expected completion time exactly.
We conjecture the asymptotic formula of Corollary 9,
based on computational experience, to be a true upper
bound. All of the non-cryptographic algorithms have
been extensively simulated, and we can say that the
present work does offer a basis upon which
implementations can be constructed. The
communications requirements of the algorithms
depend heavily on the underlying implementation of
the secure sum algorithm.
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