With the increasing volume of images users share through social sites, maintaining privacy has become a major problem, as demonstrated by a recent wave of publicized incidents where users inadvertently shared personal information.
PRIVACY POLICY INFERENCE OF USER-UPLOADED IMAGES ON CONTENT SHARING SITESShakas Technologies
This document describes a proposed system called Adaptive Privacy Policy Prediction (A3P) that aims to automatically generate personalized privacy policies for images uploaded by users to social media sites. The system considers several factors that may influence privacy preferences, including social context, image content, metadata, and changes in individual privacy attitudes over time. It uses a two-stage approach involving image classification and adaptive policy prediction. Images are first classified based on content and metadata, then policies for similar images are analyzed to predict policies for new images. The system is evaluated on over 5,000 policies with over 90% accuracy.
The document proposes an Adaptive Privacy Policy Prediction (A3P) system to automatically generate personalized privacy policies for images uploaded by users to content sharing sites. The system considers several factors that influence privacy preferences, including social context, image content and metadata. It uses a two-level framework where newly uploaded images are first classified into categories, then a policy prediction algorithm generates a recommended policy based on the image category and the user's history. Evaluation shows the system achieves over 90% accuracy in predicting privacy policies.
This document analyzes and compares the privacy policies of three social media platforms: Flickr, Instagram, and Pinterest. It summarizes each platform's privacy policy, noting what user information is collected and how it is used. It also compares the policies, finding similarities around basic user information collection and allowing third parties access to data. Differences include Flickr allowing custom photo privacy settings while the others do not, and how each handles the "follow" feature. The document raises questions about account deletion and how blocking works on the platforms.
Privacy Policy Inference of User-Uploaded Images on Content Sharing Sites1crore 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
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Implementation of Privacy Policy Specification System for User Uploaded Image...rahulmonikasharma
This document presents a proposed privacy policy specification system to help users control access to images shared over social media sites. The system would allow users to create groups, apply privacy policies (e.g. commenting, sharing, expiration, downloading) to each group, and then share images with specific groups so that the assigned group policies are applied to each image. This is intended to address limitations of existing systems that may inaccurately generate privacy policies if image metadata is unavailable or manually created. The proposed system aims to give users more control over privacy policies for shared images within designated groups on social media sites.
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.
PRIVACY POLICY INFERENCE OF USER-UPLOADED IMAGES ON CONTENT SHARING SITESShakas Technologies
This document describes a proposed system called Adaptive Privacy Policy Prediction (A3P) that aims to automatically generate personalized privacy policies for images uploaded by users to social media sites. The system considers several factors that may influence privacy preferences, including social context, image content, metadata, and changes in individual privacy attitudes over time. It uses a two-stage approach involving image classification and adaptive policy prediction. Images are first classified based on content and metadata, then policies for similar images are analyzed to predict policies for new images. The system is evaluated on over 5,000 policies with over 90% accuracy.
The document proposes an Adaptive Privacy Policy Prediction (A3P) system to automatically generate personalized privacy policies for images uploaded by users to content sharing sites. The system considers several factors that influence privacy preferences, including social context, image content and metadata. It uses a two-level framework where newly uploaded images are first classified into categories, then a policy prediction algorithm generates a recommended policy based on the image category and the user's history. Evaluation shows the system achieves over 90% accuracy in predicting privacy policies.
This document analyzes and compares the privacy policies of three social media platforms: Flickr, Instagram, and Pinterest. It summarizes each platform's privacy policy, noting what user information is collected and how it is used. It also compares the policies, finding similarities around basic user information collection and allowing third parties access to data. Differences include Flickr allowing custom photo privacy settings while the others do not, and how each handles the "follow" feature. The document raises questions about account deletion and how blocking works on the platforms.
Privacy Policy Inference of User-Uploaded Images on Content Sharing Sites1crore 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
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Implementation of Privacy Policy Specification System for User Uploaded Image...rahulmonikasharma
This document presents a proposed privacy policy specification system to help users control access to images shared over social media sites. The system would allow users to create groups, apply privacy policies (e.g. commenting, sharing, expiration, downloading) to each group, and then share images with specific groups so that the assigned group policies are applied to each image. This is intended to address limitations of existing systems that may inaccurately generate privacy policies if image metadata is unavailable or manually created. The proposed system aims to give users more control over privacy policies for shared images within designated groups on social media sites.
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.
A Survey On Privacy Policy Inference for Social ImagesIRJET Journal
This document summarizes research on privacy issues related to sharing photos and content on social networks. It discusses how improved technology has led to increased privacy violations as users share large volumes of images with many people. The document reviews existing approaches to automating privacy settings for shared content, but notes that these may be insufficient for addressing unique privacy needs of images. It proposes generating user profiles and maintaining privacy inference policies based on user profiles, image content and metadata. The goal is to develop better systems to help users easily configure privacy settings for images shared on social networks.
IEEE Projects 2015 | Privacy policy inference of user uploaded images on cont...1crore 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
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Multi-Mode Conceptual Clustering Algorithm Based Social Group Identification ...inventionjournals
The problem of web search time complexity and accuracy has been visited in many research papers, and the authors discussed many approaches to improve the search performance. Still the approaches does not produce any noticeable improvement and struggles with more time complexity as well. To overcome the issues identified, an efficient multi mode conceptual clustering algorithm has been discussed in this paper, which identifies the similar interested user groups by clustering their search context according to different conceptual queries. Identified user groups are shared with the related conceptual queries and their results to reduce the time complexity. The multi mode conceptual clustering, performs grouping of search queries and users according to number of users and their search pattern. The concept of search is identified by using Natural language processing methods and the web logs produced by the default web search engines. The author designed a dedicated web interface to collect the web log about the user search and the same data has been used to cluster the social groups according to number of conceptual queries. The search results has been shared between the users of identified social groups which reduces the search time complexity and improves the efficiency of web search in better manner
Detecting Spam Tags Against Collaborative Unfair Through Trust ModellingIOSR Journals
This document discusses methods for detecting spam tags in collaborative tagging systems through trust modeling. It classifies existing approaches into content trust modeling and user trust modeling. Content trust modeling assigns trust scores to content based on tags and users associated with it, while user trust modeling assigns trust scores to users based on their tagging behavior. The document also discusses challenges like evaluating models on multilingual data and lack of publicly available datasets for comparison. It concludes that trust modeling is important for enhancing reliability of social networks and content sharing services.
Social Re-Ranking using Tag Based Image SearchIRJET Journal
This document proposes a social re-ranking system for tag-based image retrieval from social media datasets. It first retrieves images based on keyword matching of the query tags. It then applies three re-ranking steps: 1) Inter-user ranking to rank images by user contributions to the query, 2) Time stamp ranking to prioritize more recent images based on title and timestamp, 3) View ranking to improve relevance by considering image view counts. An experiment on a social image dataset showed the method effectively and efficiently retrieves more relevant and diverse images compared to other tag-based image ranking methods.
Authorization mechanism for multiparty data sharing in social networkeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
YOURPRIVACYPROTECTOR: A RECOMMENDER SYSTEM FOR PRIVACY SETTINGS IN SOCIAL NET...ijsptm
Ensuring privacy of users of social networks is probably an unsolvable conundrum. At the same time, an informed use of the existing privacy options by the social network participants may alleviate - or even prevent - some of the more drastic privacy-averse incidents. Unfortunately, recent surveys show that an average user is either not aware of these options or does not use them, probably due to their perceived complexity. It is therefore reasonable to believe that tools assisting users with two tasks: 1) understanding their social net behaviour in terms of their privacy settings and broad privacy categories, and 2)recommending reasonable privacy options, will be a valuable tool for everyday privacy practice in a social
network context. This paper presents YourPrivacyProtector, a recommender system that shows how simple machine learning techniques may provide useful assistance in these two tasks to Facebook users. We support our claim with empirical results of application of YourPrivacyProtector to two groups of Facebook
users.
Personalized geo tag recommendation for community contributed imageseSAT Journals
Abstract Tagging is popularized by many social sharing websites, which allows us to add the description to object. Using tags users can organize their data so that it will be helpful for searching and browsing. Geotagging of a photo is the process in which a photo is marked with the geographical identification of the place it was taken. Geotagging can benefit users, to discover an Extensive Variation of exact Location related information. In personalized tag recommendation, tags that are relevant to the user's query are retrieved based upon the user's interest. The introduction of the Hypergraph learning is to find joint relevance between the visual and textual domains. Given a photo with Geolocation and without tags, System uses nearest neighbour search to obtain some user- predilected tags and geo-location predilected tags individually. It discovers the semantically and visually related images, and explores the idea of annotation-by-search to recommend tags for the untagged photo. In conclusion, the tags are recommended to the user. Keywords: Hypergraph Construction, Hypergraph learning, Personalization, Geo-tags, Preference learning
Protecting location privacy in sensor networks against a global eavesdropperShakas Technologies
The document discusses techniques for providing location privacy in sensor networks against a global eavesdropper. It proposes four techniques - periodic collection, source simulation, sink simulation, and backbone flooding - to provide location privacy for monitored objects (source location privacy) and data sinks (sink location privacy). These techniques provide trade-offs between privacy, communication cost, and latency. Analysis and simulation demonstrate that the proposed techniques are efficient and effective for providing source and sink location privacy in sensor networks.
Circuit ciphertext policy attribute-based hybrid encryption with verifiable d...Shakas Technologies
In the cloud, for achieving access control and keeping data confidential, the data owners could adopt attribute-based encryption to encrypt the stored data.
PANDA: PUBLIC AUDITING FOR SHARED DATA WITH EFFICIENT USER REVOCATION IN THE ...Shakas Technologies
This paper proposes a public auditing mechanism called Panda that allows for efficient user revocation in shared data stored in the cloud. Existing mechanisms require re-signing data blocks signed by a revoked user, which is inefficient. Panda utilizes proxy re-signatures to allow the cloud to re-sign these blocks on behalf of existing users, improving efficiency and reducing users' computation and communication costs. A public verifier can still audit integrity of shared data, even if parts were re-signed by the cloud. Panda also supports batch auditing of multiple tasks and can scale to large user groups and data sizes.
CONTROL CLOUD DATA ACCESS PRIVILEGE AND ANONYMITY WITH FULLY ANONYMOUS ATTRIB...Shakas Technologies
This document describes a proposed system called AnonyControl and AnonyControl-F that aims to securely manage access privileges for cloud data while preserving user identity privacy. It discusses shortcomings of existing systems in controlling privileges and protecting user identities. The proposed systems decentralize authority to limit identity leakage, generalize access control to manage privileges, and fully prevent identity leakage in AnonyControl-F. Security analysis shows the schemes are secure under certain assumptions, and performance evaluation shows feasibility. Key aspects include attribute-based encryption, multiple authorities dividing attribute sets, and techniques like oblivious transfer to issue keys without authorities learning user attributes.
This document discusses privacy-preserving access control for data stored in public clouds. It proposes a two-layer encryption approach where the data owner performs coarse-grained encryption and the cloud performs fine-grained encryption based on access control policies. This delegates access control enforcement to the cloud while preserving data confidentiality and user privacy. Existing single-layer encryption approaches burden the data owner with all encryption tasks. The two-layer approach more efficiently handles policy and user changes by only updating the outer encryption layer at the cloud.
Effective key management in dynamic wireless sensor networksShakas Technologies
Recently, wireless sensor networks (WSNs) have been deployed for a wide variety of applications, including military sensing and tracking, patient status monitoring, traffic flow monitoring, where sensory devices often move between different locations.
K nearest neighbor classification over semantically secure encryptedShakas Technologies
Data Mining has wide applications in many areas such as banking, medicine, scientific research and among government agencies. Classification is one of the commonly used tasks in data mining applications.
Passive ip traceback disclosing the locations of ip spoofers from path backscShakas Technologies
It is long known attackers may use forged source IP address to conceal their real locations. To capture the spoofers, a number of IP traceback mechanisms have been proposed. However, due to the challenges of deployment, there has been not a widely adopted IP traceback solution, at least at the Internet level.
Key updating for leakage resiliency with application to aes modes of operationShakas Technologies
Side-channel analysis (SCA) exploits the information leaked through unintentional outputs (e.g., power consumption) to reveal the secret key of cryptographic modules. The real threat of SCA lies in the ability to mount attacks over small parts of the key and to aggregate information over different encryptions.
A profit maximization scheme with guaranteed quality of service in cloud comp...Shakas Technologies
A HYBRID CLOUD APPROACH FOR SECURE AUTHORIZED DEDUPLICATION
ABSTRACT:
Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. To protect the confidentiality of sensitive data while supporting reduplication, the convergent encryption technique has been proposed to encrypt the data before outsourcing.
Friendbook a semantic based friend recommendation system for social networksShakas Technologies
Existing social networking services recommend friends to users based on their social graphs, which may not be the most appropriate to reflect a user’s preferences on friend selection in real life. In this paper, we present Friend book, a novel semantic based friend recommendation system for social networks, which recommends friends to users based on their life styles instead of social graphs.
Entity linking with a knowledge baseissues, techniques, and solutionsShakas Technologies
The large number of potential applications from bridging Web data with knowledge bases has led to an increase in the entity linking research. Entity linking is the task to link entity mentions in text with their corresponding entities in a knowledgebase.
Identity based encryption with outsourced revocation in cloud computingShakas Technologies
The document proposes a new approach to identity-based encryption with outsourced revocation. It introduces a key update cloud service provider that handles most key generation operations, leaving only simple tasks for the private key generator and users. This offloads computation costs. A hybrid private key combines identity and time components, allowing efficient key updates to revoke users. The scheme achieves constant efficiency while removing the need for users to directly interact with the private key generator during key updates. An advanced construction based on the refereed delegation of computation model provides additional security.
A Survey On Privacy Policy Inference for Social ImagesIRJET Journal
This document summarizes research on privacy issues related to sharing photos and content on social networks. It discusses how improved technology has led to increased privacy violations as users share large volumes of images with many people. The document reviews existing approaches to automating privacy settings for shared content, but notes that these may be insufficient for addressing unique privacy needs of images. It proposes generating user profiles and maintaining privacy inference policies based on user profiles, image content and metadata. The goal is to develop better systems to help users easily configure privacy settings for images shared on social networks.
IEEE Projects 2015 | Privacy policy inference of user uploaded images on cont...1crore 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
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Multi-Mode Conceptual Clustering Algorithm Based Social Group Identification ...inventionjournals
The problem of web search time complexity and accuracy has been visited in many research papers, and the authors discussed many approaches to improve the search performance. Still the approaches does not produce any noticeable improvement and struggles with more time complexity as well. To overcome the issues identified, an efficient multi mode conceptual clustering algorithm has been discussed in this paper, which identifies the similar interested user groups by clustering their search context according to different conceptual queries. Identified user groups are shared with the related conceptual queries and their results to reduce the time complexity. The multi mode conceptual clustering, performs grouping of search queries and users according to number of users and their search pattern. The concept of search is identified by using Natural language processing methods and the web logs produced by the default web search engines. The author designed a dedicated web interface to collect the web log about the user search and the same data has been used to cluster the social groups according to number of conceptual queries. The search results has been shared between the users of identified social groups which reduces the search time complexity and improves the efficiency of web search in better manner
Detecting Spam Tags Against Collaborative Unfair Through Trust ModellingIOSR Journals
This document discusses methods for detecting spam tags in collaborative tagging systems through trust modeling. It classifies existing approaches into content trust modeling and user trust modeling. Content trust modeling assigns trust scores to content based on tags and users associated with it, while user trust modeling assigns trust scores to users based on their tagging behavior. The document also discusses challenges like evaluating models on multilingual data and lack of publicly available datasets for comparison. It concludes that trust modeling is important for enhancing reliability of social networks and content sharing services.
Social Re-Ranking using Tag Based Image SearchIRJET Journal
This document proposes a social re-ranking system for tag-based image retrieval from social media datasets. It first retrieves images based on keyword matching of the query tags. It then applies three re-ranking steps: 1) Inter-user ranking to rank images by user contributions to the query, 2) Time stamp ranking to prioritize more recent images based on title and timestamp, 3) View ranking to improve relevance by considering image view counts. An experiment on a social image dataset showed the method effectively and efficiently retrieves more relevant and diverse images compared to other tag-based image ranking methods.
Authorization mechanism for multiparty data sharing in social networkeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
YOURPRIVACYPROTECTOR: A RECOMMENDER SYSTEM FOR PRIVACY SETTINGS IN SOCIAL NET...ijsptm
Ensuring privacy of users of social networks is probably an unsolvable conundrum. At the same time, an informed use of the existing privacy options by the social network participants may alleviate - or even prevent - some of the more drastic privacy-averse incidents. Unfortunately, recent surveys show that an average user is either not aware of these options or does not use them, probably due to their perceived complexity. It is therefore reasonable to believe that tools assisting users with two tasks: 1) understanding their social net behaviour in terms of their privacy settings and broad privacy categories, and 2)recommending reasonable privacy options, will be a valuable tool for everyday privacy practice in a social
network context. This paper presents YourPrivacyProtector, a recommender system that shows how simple machine learning techniques may provide useful assistance in these two tasks to Facebook users. We support our claim with empirical results of application of YourPrivacyProtector to two groups of Facebook
users.
Personalized geo tag recommendation for community contributed imageseSAT Journals
Abstract Tagging is popularized by many social sharing websites, which allows us to add the description to object. Using tags users can organize their data so that it will be helpful for searching and browsing. Geotagging of a photo is the process in which a photo is marked with the geographical identification of the place it was taken. Geotagging can benefit users, to discover an Extensive Variation of exact Location related information. In personalized tag recommendation, tags that are relevant to the user's query are retrieved based upon the user's interest. The introduction of the Hypergraph learning is to find joint relevance between the visual and textual domains. Given a photo with Geolocation and without tags, System uses nearest neighbour search to obtain some user- predilected tags and geo-location predilected tags individually. It discovers the semantically and visually related images, and explores the idea of annotation-by-search to recommend tags for the untagged photo. In conclusion, the tags are recommended to the user. Keywords: Hypergraph Construction, Hypergraph learning, Personalization, Geo-tags, Preference learning
Protecting location privacy in sensor networks against a global eavesdropperShakas Technologies
The document discusses techniques for providing location privacy in sensor networks against a global eavesdropper. It proposes four techniques - periodic collection, source simulation, sink simulation, and backbone flooding - to provide location privacy for monitored objects (source location privacy) and data sinks (sink location privacy). These techniques provide trade-offs between privacy, communication cost, and latency. Analysis and simulation demonstrate that the proposed techniques are efficient and effective for providing source and sink location privacy in sensor networks.
Circuit ciphertext policy attribute-based hybrid encryption with verifiable d...Shakas Technologies
In the cloud, for achieving access control and keeping data confidential, the data owners could adopt attribute-based encryption to encrypt the stored data.
PANDA: PUBLIC AUDITING FOR SHARED DATA WITH EFFICIENT USER REVOCATION IN THE ...Shakas Technologies
This paper proposes a public auditing mechanism called Panda that allows for efficient user revocation in shared data stored in the cloud. Existing mechanisms require re-signing data blocks signed by a revoked user, which is inefficient. Panda utilizes proxy re-signatures to allow the cloud to re-sign these blocks on behalf of existing users, improving efficiency and reducing users' computation and communication costs. A public verifier can still audit integrity of shared data, even if parts were re-signed by the cloud. Panda also supports batch auditing of multiple tasks and can scale to large user groups and data sizes.
CONTROL CLOUD DATA ACCESS PRIVILEGE AND ANONYMITY WITH FULLY ANONYMOUS ATTRIB...Shakas Technologies
This document describes a proposed system called AnonyControl and AnonyControl-F that aims to securely manage access privileges for cloud data while preserving user identity privacy. It discusses shortcomings of existing systems in controlling privileges and protecting user identities. The proposed systems decentralize authority to limit identity leakage, generalize access control to manage privileges, and fully prevent identity leakage in AnonyControl-F. Security analysis shows the schemes are secure under certain assumptions, and performance evaluation shows feasibility. Key aspects include attribute-based encryption, multiple authorities dividing attribute sets, and techniques like oblivious transfer to issue keys without authorities learning user attributes.
This document discusses privacy-preserving access control for data stored in public clouds. It proposes a two-layer encryption approach where the data owner performs coarse-grained encryption and the cloud performs fine-grained encryption based on access control policies. This delegates access control enforcement to the cloud while preserving data confidentiality and user privacy. Existing single-layer encryption approaches burden the data owner with all encryption tasks. The two-layer approach more efficiently handles policy and user changes by only updating the outer encryption layer at the cloud.
Effective key management in dynamic wireless sensor networksShakas Technologies
Recently, wireless sensor networks (WSNs) have been deployed for a wide variety of applications, including military sensing and tracking, patient status monitoring, traffic flow monitoring, where sensory devices often move between different locations.
K nearest neighbor classification over semantically secure encryptedShakas Technologies
Data Mining has wide applications in many areas such as banking, medicine, scientific research and among government agencies. Classification is one of the commonly used tasks in data mining applications.
Passive ip traceback disclosing the locations of ip spoofers from path backscShakas Technologies
It is long known attackers may use forged source IP address to conceal their real locations. To capture the spoofers, a number of IP traceback mechanisms have been proposed. However, due to the challenges of deployment, there has been not a widely adopted IP traceback solution, at least at the Internet level.
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PRIVACY POLICY INFERENCE OF USER-UPLOADED IMAGES ON CONTENT SHARING SITESnexgentechnology
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PRIVACY POLICY INFERENCE OF USER-UPLOADED IMAGES ON CONTENT SHARING SITES - I...Nexgen Technology
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Privacy policy inference of user uploadednexgentech15
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iaetsd Adaptive privacy policy prediction for user uploaded images onIaetsd Iaetsd
This document proposes an Adaptive Privacy Policy Prediction (A3P) system to help users set privacy policies for images uploaded to social media sites. The system includes two main components: A3P-Core and A3P-Social. A3P-Core classifies images and predicts policies based on image content and user history. A3P-Social predicts policies based on a user's social context when A3P-Core cannot, such as for new users. It groups users with similar social attributes and privacy preferences to identify communities to reference for policy recommendations. The system was evaluated against alternative approaches and showed improved accuracy in predicting privacy policies for uploaded images.
Ijricit 01-008 confidentiality strategy deduction of user-uploaded pictures o...Ijripublishers Ijri
With the growing quantity of pictures users distribute from node to node social networks, retaining confidentiality has turn out to be a foremost predicament, as declared by a latest wave of made known occurrences wherever users unintentionally shared individual profile. In radiance of these occurrences made necessitate of tools to assist users organize access to their distributed data is evident. In the direction of speak to this requirement, we suggest an Adaptive Privacy Policy forecast (A3P) scheme to facilitate users compile confidentiality settings for their pictures. We observe the responsibility of communal context, picture content, and metadata as possible sign of users’ confidentiality preference. We recommend a two-level structure which according to the user’s obtainable times past on the site, establishs the most excellent obtainable confidentiality policy for the user’s pictures being uploaded. Our solution relies on an image classification framework for image categories which may be associated with similar policies, and on a policy prediction algorithm to automatically generate a policy for each newly uploaded image, also according to users’ social features. Over time, the generated policies will follow the evolution of users’ privacy attitude. We provide the results of our extensive evaluation over 5,000 policies, which demonstrate the effectiveness of our system, with prediction accuracies over 90 percent.
Adaptive Privacy Policy Prediction of User Uploaded Images on Content sharing...IJERA Editor
User Image sharing social site maintaining privacy has become a major problem, as demonstrated by a recent
wave of publicized incidents where users inadvertently shared personal information. In light of these incidents,
the need of tools to help users control access to their shared content is apparent. Toward addressing this need an
Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. The
solution relies on an image classification framework for image categories which may be associated with similar
policies and on a policy prediction algorithm to automatically generate a policy for each newly uploaded image,
also according to user’s social features. Image Sharing takes place both among previously established groups of
known people or social circles and also increasingly with people outside the users social circles, for purposes of
social discovery-to help them identify new peers and learn about peers interests and social surroundings,
Sharing images within online content sharing sites, therefore, may quickly lead to unwanted disclosure. The
aggregated information can result in unexpected exposure of one’s social environment and lead to abuse of
one’s personal information.
User service-rating-prediction-by-exploring social users rating BehavioursShakas Technologies
This document proposes a user-service rating prediction approach that explores social users' rating behaviors. It focuses on aspects of users' rating behaviors like when they rate items, what the ratings and items are, and how ratings diffuse among social friends. The approach represents rating schedules and models interpersonal rating diffusion. It fuses personal interest factors, interpersonal interest similarity, rating behavior similarity, and rating diffusion into a matrix factorization framework. The proposed approach aims to address limitations of existing collaborative filtering recommender systems like increased computational costs, lack of privacy, and insecure computations.
This document discusses query aware determinization of uncertain objects. It proposes determinizing probabilistic data to enable storage in legacy systems that only accept deterministic data. Existing approaches like thresholding or top-1 selection for determinization lead to suboptimal query performance. The document proposes a query-aware strategy to determinize probabilistic data in a way that optimizes query workload quality, outperforming existing solutions. It aims to generate the best deterministic representation of probabilistic data for use in legacy applications that require deterministic input.
This paper addresses the problem of determinizing probabilistic data to enable storage in legacy systems that only accept deterministic data. The paper explores this problem in the context of triggers and selection queries. Existing approaches like thresholding or top-1 selection are shown to provide suboptimal performance. Instead, the paper develops a query-aware strategy and demonstrates its advantages over existing solutions through empirical evaluation on real and synthetic datasets.
Adaptive Search Based On User Tags in Social NetworkingIOSR Journals
This document summarizes an article about adaptive search based on user tags in social networking. It discusses using tags that users apply to images in social media sites like Flickr to improve image search and personalize results. It proposes using topic models to identify different meanings of ambiguous tags and a user's interests to display more relevant images. The framework involves reranking images based on aesthetics scores predicted from user comments, and using tag-based and group-based metadata to discover topics and personalize search results. Future work could further analyze community-generated metadata to identify interests and refine search algorithms.
Predicting Privacy Policy Automatically To the User Uploaded Images on Conten...IJMTST Journal
Nowadays sharing of images is increasing through social networking sites but maintaining privacy is a major problem. While sharing images users knowingly or unknowingly share their personal information. Due to these incidents, there is a need of tool for setting privacy for their images. To address this need we propose an adaptive privacy policy prediction (A3P) to set privacy for their images. We are considering the metadata for predicting the privacy. Our Solution depends on image classification for image categories and predicting privacy.
My Privacy My decision: Control of Photo Sharing on Online Social NetworksIRJET Journal
This document summarizes a research paper that proposes a facial recognition system to help users control photo sharing on social networks while protecting privacy. It discusses how photo sharing on social networks can unintentionally reveal private user information through tags, comments or metadata. The proposed system would recognize faces in photos and allow users to choose privacy settings during the photo posting process. It would also use private user photos to train the facial recognition model while preserving privacy through a distributed consensus method. The goal is to give users more awareness and control over how their photos are shared and help prevent unintended disclosure of personal information.
Nowadays Social Media focus on users to billions of images, famous e commerce web sites such as Flipkart, Amazon etc. Tag-primarily based definitely image are seeking for is an essential method to find photos shared with the aid of manner of clients in social networks. But, a manner to make the top ranked result applicable and with range is difficult. In this paper, we advocate a topic diverse ranking method for tag-primarily based photo retrieval with the eye of selling the situation insurance overall performance. First, we bring together a tag graph based totally absolutely at the similarity among every tag. Then network detection approach is accomplished to mine the subject community of every tag. After that, inter-community and intra-network ranking are added to gather the very last retrieved results. Inside the inter-network rating way, an adaptive random stroll model is employed to rank the network primarily based at the multi-information of every topic community D. Dhayalan | M. Queen Mary Vidya | B. Gowri Priya "Image Tagging With Social Assistance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Active Galaxy , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd14566.pdf
http://www.ijtsrd.com/engineering/computer-engineering/14566/image-tagging-with-social-assistance/d-dhayalan
Detecting and Providing Solutions to Privacy Issues in Social MediaIRJET Journal
The document discusses detecting and resolving privacy issues that arise when sharing content like photos and posts on social media. It proposes a mechanism that can identify conflicts between the different privacy preferences of users involved with a shared item. The mechanism aims to provide a solution to resolve the conflicts in a way that satisfies all users. It does this by comparing the privacy priorities of each user and determining who can access the item in a way that adapts to different user preferences. The proposed system was tested against existing methods and found to better match how users would manually resolve conflicts based on their willingness to make concessions.
Socially Shared Images with Automated Annotation Process by Using Improved Us...IJERA Editor
Objectives: The main objective of this research is to increase the semantic concepts prominently as well as
reduce the searching time complexity. This is also aimed to ensure the higher privacy with security and develop
the accurate privacy policy generation.
Methods: The existing method named as adaptive privacy policy prediction (A3P) is used to discover the best
available privacy policy for the user’s image being uploaded. The proposed method name as improved semantic
annotated markovian semantic Indexing (ISMSI) is used for retrieving the images semantically.
Findings: The proposed method achieves high performance in terms of greater accuracy values.
Application/Improvements: The proposed system is done by using semantic annotated markovian semantic
Indexing (ISMSI) approach. ISMSI method is used for identification of similarity as well as semantic annotated
images and improves the privacy significantly.
A Survey on Multi-party Privacy Disputes in Social NetworksIRJET Journal
This document discusses privacy issues that can arise when multiple users are involved in sharing content on social media. It proposes a new mechanism to detect and resolve conflicts between users' privacy preferences regarding shared content. A user study found that the proposed mechanism was better able to match how users would manually resolve conflicts than existing approaches. The mechanism models different situations where users may be willing to concede their privacy preferences and aims to find a solution that is acceptable to all involved users in an automated way, reducing the need for manual intervention.
Relevance feedback a novel method to associate user subjectivity to imageIAEME Publication
This document proposes a novel method for combining user subjectivity and relevance feedback in content-based image retrieval systems. It describes a two-step process: 1) Performing image analysis to automatically infer the best combination of models to represent the data of interest to the user, and 2) Capturing the user's high-level query and perceptual subjectivity through dynamically updated weights based on the user's feedback during the retrieval process. The proposed approach aims to reduce the user's effort in composing queries and better capture their information needs over time by continuously learning from user interactions.
PRIVACY PRESERVATION IN SOCIAL MEDIA BY IMAGE PROCESSINGAM Publications
Photo sharing is a captivating feature which popularizes Online Gregarious Networks (OSNs). Lamentably, it may leak users’ privacy if they are sanctioned to post, comment, and tag a photo liberatingly. In this paper, we endeavor to address this issue and study the scenario when a utilizer shares a photo containing individuals other than him/her (termed co-photo for short). To obviate possible privacy leakage of a photo, we design a mechanism to enable each individual in a photo be cognizant of the posting activity and participate in the decision making on the photo posting. For this purport, we require an efficient facial apperception (FR) system that can apperceive everyone in the photo. However, more authoritatively mandating privacy setting may limit the number of the photos publicly available to train the FR system. To deal with this dilemma, our mechanism endeavors to utilize users’ private photos to design a personalized FR system concretely trained to differentiate possible photo co-owners without leaking their privacy. We additionally develop a distributed consensus predicated method to reduce the computational intricacy and for fend the private training set. We show that our system is superior to other possible approaches in terms of apperception ratio and efficiency. Our mechanism is implemented as a proof of concept Android application on Facebook’s platform.
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Privacy policy inference of user uploaded
1. 1.
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PRIVACY POLICY INFERENCE OF USER-UPLOADED
IMAGES ON CONTENT SHARING SITES
ABSTRACT
With the increasing volume of images users share through social sites, maintaining
privacy has become a major problem, as demonstrated by a recent wave of publicized incidents
where users inadvertently shared personal information. In light of these incidents, the need of
tools to help users control access to their shared content is apparent. Toward addressing this
need, we propose an Adaptive Privacy Policy Prediction (A3P) system to help users compose
privacy settings for their images. We examine the role of social context, image content, and
metadata as possible indicators of users’ privacy preferences. We propose a two-level framework
which according to the user’s available history on the site, determines the best available privacy
policy for the user’s images being uploaded. Our solution relies on an image classification
framework for image categories which may be associated with similar policies, and on a policy
prediction algorithm to automatically generate a policy for each newly uploaded image, also
according to users’ social features. Over time, the generated policies will follow the evolution of
users’ privacy attitude. We provide the results of our extensive evaluation over 5,000 policies,
which demonstrate the effectiveness of our system, with prediction accuracies over 90 percent.
2. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
EXISTING SYSTEM:
Several recent works have studied how to automate the task of privacy settings Bonneau
et al. proposed the concept of privacy suites which recommend to users a suite of privacy
settings that n“expert” users or other trusted friends have already set, so that normal users can
either directly choose a setting or only need to do minor modification. Similarly, Danezis
proposed a machine-learning based approach to automatically extract privacy settings from the
social context within which the data is produced. Parallel to the work of Danezis, Adu-Oppong et
al. develop privacy settings based on a concept of “Social Circles” which consist of clusters of
friends formed by partitioning users’ friend lists. Ravichandran et al. studied how to predict a
user’s privacy preferences for location-based data (i.e., share her location or not) based on
location and time of day. Fang et al. proposed a privacy wizard to help users grant privileges to
their friends. The wizard asks users to first assign privacy labels to selected friends, and then
uses this as input to construct a classifier which classifies friends based on their profiles and
automatically assign privacy labels to the unlabeled friends. More recently, Klemperer et al.
studied whether the keywords and captions with which users tag their photos can be used to help
users more intuitively create and maintain access-control policies. Their findings are inline with
our approach: tags created for organizational purposes can be repurposed to help create
reasonably accurate access-control rules.
3. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
PROPOSED SYSTEM:
We propose an Adaptive Privacy Policy Prediction (A3P) system which aims to provide
users a hassle free privacy settings experience by automatically generating personalized policies.
The A3P system handles user uploaded images, and factors in the following criteria that
influence one’s privacy settings of images: The impact of social environment and personal
characteristics. Social context of users, such as their profile information and relationships with
others may provide useful information regarding users’ privacy preferences. For example, users
interested in photography may like to share their photos with other amateur photographers. Users
who have several family members among their social contacts may share with them pictures
related to family events. However, using common policies across all users or across users with
similar traits may be too simplistic and not satisfy individual preferences. Users may have
drastically different opinions even on the same type of images. For example, a privacy adverse
person may be willing to share all his personal images while a more conservative person may
just want to share personal images with his family members. In light of these considerations, it is
important to find the balancing point between the impact of social environment and users’
individual characteristics in order to predict the policies that match each individual’s needs.
Moreover, individuals may change their overall attitude toward privacy as time passes. In order
to develop a personalized policy recommendation system, such changes on privacy opinions
should be carefully considered. The role of image’s content and metadata. In general, similar
images often incur similar privacy preferences, especially when people appear in the images. For
example, one may upload several photos of his kids and specify that only his family members are
allowed to see these photos. He may upload some other photos of landscapes which he took as a
hobby and for these photos, he may set privacy preference allowing anyone to view and
comment the photos. Analyzing the visual content may not be sufficient to capture users’ privacy
preferences. Tags and other metadata are indicative of the social context of the image, including
where it was taken and why , and also provide a synthetic description of images, complementing
the information obtained from visual content analysis.
4. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
Module 1
A3P-CORE
There are two major components in A3P-core: (i) Image classification and (ii) Adaptive
policy prediction. For each user, his/her images are first classified based on content and
metadata. Then, privacy policies of each category of images are analyzed for the policy
prediction. Adopting a two-stage approach is more suitable for policy recommendation than
applying the common one-stage data mining approaches to mine both image features and
policies together. Recall that when a user uploads a new image, the user is waiting for a
recommended policy. The two-stage approach allows the system to employ the first stage to
classify the new image and find the candidate sets of images for the subsequent policy
recommendation. As for the one-stage mining approach, it would not be able to locate the right
class of the new image because its classification criteria needs both image features and policies
whereas the policies of the new image are not available yet. Moreover, combining both image
features and policies into a single classifier would lead to a system which is very dependent to
the specific syntax of the policy. If a change in the supported policies were to be introduced, the
whole learning model would need to change.
Module 2
Image Classification
To obtain groups of images that may be associated with similar privacy preferences, we
propose a hierarchical image classification which classifies images first based on their contents
and then refine each category into subcategories based on their metadata. Images that do not
have metadata will be grouped only by content. Such a hierarchical classification gives a higher
priority to image content and minimizes the influence of missing tags. Note that it is possible that
some images are included in multiple categories as long as they contain the typical content
features or metadata of those categories. The content-based classification creates two categories:
“landscape” and “kid”. Images C, D, E and F are included in both categories as they show kids
playing outdoor which satisfy the two themes: “landscape” and “kid”. These two categories are
further divided into subcategories based on tags associated with the images. As a result, we
5. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
obtain two subcategories under each theme respectively. Notice that image G is not shown in any
subcategory as it does not have any tag; image A shows up in both subcategories because it has
tags indicating both “beach” and “wood”.
Module 3
Policy Mining
We propose a hierarchical mining approach for policy mining. Our approach leverages
association rule mining techniques to discover popular patterns in policies. Policy mining is
carried out within the same category of the new image because images in the same category are
more likely under the similar level of privacy protection. The basic idea of the hierarchical
mining is to follow a natural order in which a user defines a policy. Given an image, a user
usually first decides who can access the image, then thinks about what specific access rights
(e.g., view only or download) should be given, and finally refine the access conditions such as
setting the expiration date. Correspondingly, the hierarchical mining first look for popular
subjects defined by the user, then look for popular actions in the policies containing the popular
subjects, and finally for popular conditions in the policies containing both popular subjects and
conditions.
Step 1: In the same category of the new image, conduct association rule mining on the subject
component of polices. Let S1, S2; . . ., denote the subjects occurring in policies. Each resultant
rule is an implication of the form X ) Y, where X, Y _ fS1, S2; . . . ; g, and X Y ¼ ;. Among the
obtained rules, we select the best rules according to one of the interestingness measures, i.e., the
generality of the rule, defined using support and confidence as introduced in [16]. The selected
rules indicate the most popular subjects (i.e., single subject) or subject combinations (i.e.,
multiple subjects) in policies. In the subsequent steps, we consider policies which contain at least
one subject in the selected rules. For clarity, we denote the set of such policies as Gsub i
corresponding to a selected rule Rsub i .
Step 2: In each policy set Gsub i , we now conduct association rule mining on the action
component. The result will be a set of association rules in the form of X ) Y, where X, Y _fopen,
comment, tag, downloadg, and X Y ¼ ;. Similar to the first step, we will select the best rules
6. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
according to the generality interestingness. This time, the selected rules indicate the most popular
combination of actions in policies with respect to each particular subject or subject combination.
Policies which do not contain any action included in the selected rules will be removed. Given a
selected rule Ract j we denote the set of remaining policies as Gact j , and note that Gact j _ Gsub
Step 3: We proceed to mine the condition component in each policy set Gact j . Let attr1, attr2,
..., attrn denote the distinct attributes in the condition component of the policies in Gact j . The
association rules are in the same format of X ) Y but with X, Y _fattr1, attr2; . . . ; attrng. Once
the rules are obtained, we again select the best rules using the generality interestingness measure.
The selected rules give us a set of attributes which often appear in policies. Similarly, we denote
the policies containing at least one attribute in the selected rule Rcon k as Gcon k and Gcon k _
Gact j
Step 4: This step is to generate candidate policies. Given Gcon k _ Gact j _ Gsub i , we consider
each corresponding series of best rules: Rcon kx , Ract jy and Rsub iz . Candidate policies are
required to possess all elements in Rcon kx , Ract jy and Rsub iz Note that candidate policies
may be different from the policies as result of Step 3. This is because Step 3 will keep policies as
long as they have one of the attributes in the selected rules.
Module 4
A3P-SOCIAL
The A3P-social employs a multi-criteria inference mechanism that generates
representative policies by leveraging key information related to the user’s social context and his
general attitude toward privacy. As mentioned earlier, A3Psocial will be invoked by the A3P-
core in two scenarios. One is when the user is a newbie of a site, and does not have enough
images stored for the A3P-core to infer meaningful and customized policies. The other is when
the system notices significant changes of privacy trend in the user’s social circle, which may be
of interest for the user to possibly adjust his/her privacy settings accordingly. In what follows,
we first present the types of social context considered by A3P-Social, and then present the policy
recommendation process.
7. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
CONCLUSION:
We have proposed an Adaptive Privacy Policy Prediction (A3P) system that helps users
automate the privacy policy settings for their uploaded images. The A3P system provides a
comprehensive framework to infer privacy preferences based on the information available for a
given user. We also effectively tackled the issue of cold-start, leveraging social context
information. Our experimental study proves that our A3P is a practical tool that offers significant
improvements over current approaches to privacy.