Pub Date : 2015-11-16DOI: 10.1109/SocialSec2015.14
Bowei Yang, Guang-hua Song, Yao Zheng, Yue Wu
Storage QoS is a key issue for a storage cloud infrastructure. This paper presents QoSC, a QoS-aware storage cloud for storing massive data over the dynamic network, based on the Hadoop distributed file system (HDFS). QoSC employs a data redundancy policy based on recovery volumes and a QoS-aware data placement strategy. We consider the QoS of a storage node as a combination of the transfer bandwidth, the availability of service, the workload (CPU utilization), and the free storage space. We have deployed QoSC on the campus network of Zhejiang University, and have conducted a group of experiments on file storage and retrieval. The experimental results show that QoSC improves the performance of file storage and retrieval and balances the workload among DataNodes, by being aware of QoS of DataNodes.
{"title":"QoSC: A QoS-Aware Storage Cloud Based on HDFS","authors":"Bowei Yang, Guang-hua Song, Yao Zheng, Yue Wu","doi":"10.1109/SocialSec2015.14","DOIUrl":"https://doi.org/10.1109/SocialSec2015.14","url":null,"abstract":"Storage QoS is a key issue for a storage cloud infrastructure. This paper presents QoSC, a QoS-aware storage cloud for storing massive data over the dynamic network, based on the Hadoop distributed file system (HDFS). QoSC employs a data redundancy policy based on recovery volumes and a QoS-aware data placement strategy. We consider the QoS of a storage node as a combination of the transfer bandwidth, the availability of service, the workload (CPU utilization), and the free storage space. We have deployed QoSC on the campus network of Zhejiang University, and have conducted a group of experiments on file storage and retrieval. The experimental results show that QoSC improves the performance of file storage and retrieval and balances the workload among DataNodes, by being aware of QoS of DataNodes.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"136 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121343156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-16DOI: 10.1109/SocialSec2015.19
Jiawen Peng, Yan Meng, Minhui Xue, Xiaojun Hei, K. Ross
The rapid growth of location-based social network (LBSN) applications -- such as WeChat, Momo, and Yik Yak -- has in essence facilitated the promotion of anonymously sharing instant messages and open discussions. These services breed a unique anonymous atmosphere for users to discover their geographic neighborhoods and then initiate private communications. In this paper, we demonstrate how such location-based features of WeChat can be exploited to determine the user's location with sufficient accuracy in any city from any location in the world. Guided by the number theory, we design and implement two generic localization attack algorithms to track anonymous users' locations that can be potentially adapted to any other LBSN services. We evaluated the performance of the proposed algorithms using Matlab simulation experiments and also deployed real-world experiments for validating our methodology. Our results show that WeChat, and other LBSN services as such, have a potential location privacy leakage problem. Finally, k-anonymity based countermeasures are proposed to mitigate the localization attacks without significantly compromising the quality-of-service of LBSN applications. We expect our research to bring this serious privacy pertinent issue into the spotlight and hopefully motivate better privacy-preserving LBSN designs.
{"title":"Attacks and Defenses in Location-Based Social Networks: A Heuristic Number Theory Approach","authors":"Jiawen Peng, Yan Meng, Minhui Xue, Xiaojun Hei, K. Ross","doi":"10.1109/SocialSec2015.19","DOIUrl":"https://doi.org/10.1109/SocialSec2015.19","url":null,"abstract":"The rapid growth of location-based social network (LBSN) applications -- such as WeChat, Momo, and Yik Yak -- has in essence facilitated the promotion of anonymously sharing instant messages and open discussions. These services breed a unique anonymous atmosphere for users to discover their geographic neighborhoods and then initiate private communications. In this paper, we demonstrate how such location-based features of WeChat can be exploited to determine the user's location with sufficient accuracy in any city from any location in the world. Guided by the number theory, we design and implement two generic localization attack algorithms to track anonymous users' locations that can be potentially adapted to any other LBSN services. We evaluated the performance of the proposed algorithms using Matlab simulation experiments and also deployed real-world experiments for validating our methodology. Our results show that WeChat, and other LBSN services as such, have a potential location privacy leakage problem. Finally, k-anonymity based countermeasures are proposed to mitigate the localization attacks without significantly compromising the quality-of-service of LBSN applications. We expect our research to bring this serious privacy pertinent issue into the spotlight and hopefully motivate better privacy-preserving LBSN designs.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129683859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-16DOI: 10.1109/SocialSec2015.20
S. Wen, Jiaojiao Jiang, Kasra Majbouri Yazdi, Y. Xiang, Wanlei Zhou
Large-degree nodes in scale-free networks are normally responsible for large cascades of epidemics. However, recent research shows small-degree nodes can also produce large-scale epidemics in the real world. In this letter, we investigate the relation between local and global influence of individuals in scale-free network in order to theoretically explain this real-world phenomenon. The local influence of an individual corresponds to the node degree, and the global influence of an individual reflects the expected number of individuals directly or indirectly influenced by this individual in epidemics. We formalize the later as the novel epidemic betweenness concept, to mathematically estimate the global influence of individuals. Our analysis shows that the global influence follows power-law distributions in scale-free networks. We also observe that the average global influence of individuals is power-law to the degree of nodes, which well explains the reason why large-degree nodes are more likely to produce large cascades of epidemics. In addition, we discover that some smalldegree nodes also possess large global influence in terms of epidemics betweenness. This well explains the counter-intuitive phenomenon in recent research.
{"title":"The Relation Between Local and Global Influence of Individuals in Scale-Free Networks","authors":"S. Wen, Jiaojiao Jiang, Kasra Majbouri Yazdi, Y. Xiang, Wanlei Zhou","doi":"10.1109/SocialSec2015.20","DOIUrl":"https://doi.org/10.1109/SocialSec2015.20","url":null,"abstract":"Large-degree nodes in scale-free networks are normally responsible for large cascades of epidemics. However, recent research shows small-degree nodes can also produce large-scale epidemics in the real world. In this letter, we investigate the relation between local and global influence of individuals in scale-free network in order to theoretically explain this real-world phenomenon. The local influence of an individual corresponds to the node degree, and the global influence of an individual reflects the expected number of individuals directly or indirectly influenced by this individual in epidemics. We formalize the later as the novel epidemic betweenness concept, to mathematically estimate the global influence of individuals. Our analysis shows that the global influence follows power-law distributions in scale-free networks. We also observe that the average global influence of individuals is power-law to the degree of nodes, which well explains the reason why large-degree nodes are more likely to produce large cascades of epidemics. In addition, we discover that some smalldegree nodes also possess large global influence in terms of epidemics betweenness. This well explains the counter-intuitive phenomenon in recent research.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126698934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the generalizing of Electronic Medical Records lots of facilities such as hospitals, insurance companies and some other government sections, accumulate large amounts of electronic data. Generally, data analysis technologies used in health insurance claims data are statistical and data mining. To get some new information from the data, the social network analysis (SNA) is proposed as a new way to explore the patientstransferring data held by Medical Insurance Bureau. In this paper, we first describe the condition of the basic medical insurance for urban and rural residents in China, then we demonstrate that the method of SNA used in the health insurance claims data can better understand the corporation among hospitals relating to patients-transferring. Particularly, this paper applies social network analysis to mine the data in three aspects: (a) community detection of hospitals network using different models. (b) the relationship among networks characteristics and healthcare quality including Length of stay(Los) in hospital, medicare cost and treatment results. (c)some interesting rules about the patients-transferring correlated with the Los and Cost.
{"title":"Find Referral Social Networks","authors":"Hao Guo, Feng Wei, Shaoyin Cheng, Fan Jiang","doi":"10.1109/SocialSec2015.8","DOIUrl":"https://doi.org/10.1109/SocialSec2015.8","url":null,"abstract":"With the generalizing of Electronic Medical Records lots of facilities such as hospitals, insurance companies and some other government sections, accumulate large amounts of electronic data. Generally, data analysis technologies used in health insurance claims data are statistical and data mining. To get some new information from the data, the social network analysis (SNA) is proposed as a new way to explore the patientstransferring data held by Medical Insurance Bureau. In this paper, we first describe the condition of the basic medical insurance for urban and rural residents in China, then we demonstrate that the method of SNA used in the health insurance claims data can better understand the corporation among hospitals relating to patients-transferring. Particularly, this paper applies social network analysis to mine the data in three aspects: (a) community detection of hospitals network using different models. (b) the relationship among networks characteristics and healthcare quality including Length of stay(Los) in hospital, medicare cost and treatment results. (c)some interesting rules about the patients-transferring correlated with the Los and Cost.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132595332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-16DOI: 10.1109/SocialSec2015.15
Cuiling Jiang, Yilin Pang, Anwen Wu
Image hash functions find extensive application in content authentication, database search, and digital forensic. This paper develops a novel robust image-hashing method based on genetic algorithm (GA) and Back Propagation (BP) Neural Network for content authentication. Lifting wavelet transform is used to extract image low frequency coefficients to create the image feature matrix. A GA-BP network model is constructed to generate image-hashing code. Experimental results demonstrate that the proposed hashing method is robust against random attack, JPEG compression, additive Gaussian noise, and so on. Receiver operating characteristics (ROC) analysis over a large image database reveals that the proposed method significantly outperforms other approaches for robust image hashing.
{"title":"A Novel Robust Image-Hashing Method for Content Authentication","authors":"Cuiling Jiang, Yilin Pang, Anwen Wu","doi":"10.1109/SocialSec2015.15","DOIUrl":"https://doi.org/10.1109/SocialSec2015.15","url":null,"abstract":"Image hash functions find extensive application in content authentication, database search, and digital forensic. This paper develops a novel robust image-hashing method based on genetic algorithm (GA) and Back Propagation (BP) Neural Network for content authentication. Lifting wavelet transform is used to extract image low frequency coefficients to create the image feature matrix. A GA-BP network model is constructed to generate image-hashing code. Experimental results demonstrate that the proposed hashing method is robust against random attack, JPEG compression, additive Gaussian noise, and so on. Receiver operating characteristics (ROC) analysis over a large image database reveals that the proposed method significantly outperforms other approaches for robust image hashing.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122586492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-16DOI: 10.1109/SocialSec2015.12
L. Hanzlik, Kamil Kluczniak, Mirosław Kutyłowski
One of the major inventions of the new personal identity cards in Germany is supporting anonymous authentication. The Restricted Identification protocol enables to authenticate in an unlimited number of domains with passwords created with strong asymmetric cryptography and not using the insecure login-password mechanism. Moreover, the RI scheme guarantees unlinkability of user's authentication in different domains. The Achilles Heel of the RI scheme is Chip Authentication procedure. The terminal must make sure that it is talking with a genuine identification card and authentication via so-called group key is used. The group key is shared by many ID's in order to create a sufficiently large anonymity set. We present an attack, where the party holding the group key and eavesdropping the communication between a card and a terminal can learn the pseudonym and later authenticate as this user in this domain. In this way the party issuing the cards may get an unlimited access to citizens accounts. We show how to solve the problem by slight changes in the protocol.
{"title":"Insecurity of Anonymous Login with German Personal Identity Cards","authors":"L. Hanzlik, Kamil Kluczniak, Mirosław Kutyłowski","doi":"10.1109/SocialSec2015.12","DOIUrl":"https://doi.org/10.1109/SocialSec2015.12","url":null,"abstract":"One of the major inventions of the new personal identity cards in Germany is supporting anonymous authentication. The Restricted Identification protocol enables to authenticate in an unlimited number of domains with passwords created with strong asymmetric cryptography and not using the insecure login-password mechanism. Moreover, the RI scheme guarantees unlinkability of user's authentication in different domains. The Achilles Heel of the RI scheme is Chip Authentication procedure. The terminal must make sure that it is talking with a genuine identification card and authentication via so-called group key is used. The group key is shared by many ID's in order to create a sufficiently large anonymity set. We present an attack, where the party holding the group key and eavesdropping the communication between a card and a terminal can learn the pseudonym and later authenticate as this user in this domain. In this way the party issuing the cards may get an unlimited access to citizens accounts. We show how to solve the problem by slight changes in the protocol.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124182039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-16DOI: 10.1109/SocialSec2015.13
Xuejiao Liu, Yingjie Xia, Yang Xiang, M. Hassan, Abdulhameed Alelaiwi
Hybrid cloud is a widely used cloud architecture in large companies that can outsource data to the public cloud, while still supporting various clients like mobile devices. However, such public cloud data outsourcing raises serious security concerns, such as how to preserve data confidentiality and how to regulate access policies to the data stored in public cloud. To address this issue, we design a hybrid cloud architecture that supports data sharing securely and efficiently, even with resource-limited devices, where private cloud serves as a gateway between the public cloud and the data user. Under such architecture, we propose an improved construction of attribute-based encryption that has the capability of delegating encryption/decryption computation, which achieves flexible access control in the cloud and privacy-preserving in datautilization even with mobile devices. Extensive experiments show the scheme can further decrease the computational cost and space overhead at the user side, which is quite efficient for the user with limited mobile devices. In the process of delegating most of the encryption/decryption computation to private cloud, the user can not disclose any information to the private cloud. We also consider the communication securitythat once frequent attribute revocation happens, our scheme is able to resist some attacks between private cloud and data user by employing anonymous key agreement.
{"title":"A Secure and Efficient Data Sharing Framework with Delegated Capabilities in Hybrid Cloud","authors":"Xuejiao Liu, Yingjie Xia, Yang Xiang, M. Hassan, Abdulhameed Alelaiwi","doi":"10.1109/SocialSec2015.13","DOIUrl":"https://doi.org/10.1109/SocialSec2015.13","url":null,"abstract":"Hybrid cloud is a widely used cloud architecture in large companies that can outsource data to the public cloud, while still supporting various clients like mobile devices. However, such public cloud data outsourcing raises serious security concerns, such as how to preserve data confidentiality and how to regulate access policies to the data stored in public cloud. To address this issue, we design a hybrid cloud architecture that supports data sharing securely and efficiently, even with resource-limited devices, where private cloud serves as a gateway between the public cloud and the data user. Under such architecture, we propose an improved construction of attribute-based encryption that has the capability of delegating encryption/decryption computation, which achieves flexible access control in the cloud and privacy-preserving in datautilization even with mobile devices. Extensive experiments show the scheme can further decrease the computational cost and space overhead at the user side, which is quite efficient for the user with limited mobile devices. In the process of delegating most of the encryption/decryption computation to private cloud, the user can not disclose any information to the private cloud. We also consider the communication securitythat once frequent attribute revocation happens, our scheme is able to resist some attacks between private cloud and data user by employing anonymous key agreement.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129610039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-16DOI: 10.1109/SocialSec2015.17
Yiping Wang, Xiaoyong Li
In cloud computing, enterprises and individual consumers can have access to storage, computing and bandwidth resources through network terminal, and do not need to install applications. Cloud computing can be divided into three categories: Software as a Service (SaaS) and Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Eucalyptus is the most widely deployed IaaS cloud service software platform in the world. It builds a cloud service layer as IaaS by using the existing infrastructure. In this article, we built the Eucalyptus cloud platform on the server, and the deployment of software Dev C++ on the Eucalyptus platform. Consumers can have remote access to the software through the Internet without installing the software in the local. Over the last few years, Big Data analysis has attracted huge attention from enterprises and research institutions. Hadoop is considered as one of the most important tools in computing development in order to tackle the Big Data. It is very convenient for Eucalyptus to create and deploy the VM instances which is provided the distributed environment on demand, where the Hadoop applications are going to be executed. So we implement Hadoop platform on Eucalyptus cloud infrastructure, and evaluate the Hadoop applications running on Eucalyptus cloud under different stressing conditions.
{"title":"Analysis of the Performance of Hadoop Applications on Eucalyptus Cloud","authors":"Yiping Wang, Xiaoyong Li","doi":"10.1109/SocialSec2015.17","DOIUrl":"https://doi.org/10.1109/SocialSec2015.17","url":null,"abstract":"In cloud computing, enterprises and individual consumers can have access to storage, computing and bandwidth resources through network terminal, and do not need to install applications. Cloud computing can be divided into three categories: Software as a Service (SaaS) and Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Eucalyptus is the most widely deployed IaaS cloud service software platform in the world. It builds a cloud service layer as IaaS by using the existing infrastructure. In this article, we built the Eucalyptus cloud platform on the server, and the deployment of software Dev C++ on the Eucalyptus platform. Consumers can have remote access to the software through the Internet without installing the software in the local. Over the last few years, Big Data analysis has attracted huge attention from enterprises and research institutions. Hadoop is considered as one of the most important tools in computing development in order to tackle the Big Data. It is very convenient for Eucalyptus to create and deploy the VM instances which is provided the distributed environment on demand, where the Hadoop applications are going to be executed. So we implement Hadoop platform on Eucalyptus cloud infrastructure, and evaluate the Hadoop applications running on Eucalyptus cloud under different stressing conditions.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129443568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tweet sentiment analysis is an important research topic. An accurate and timely analysis report could give good indications on the general public's opinions. After reviewing the current research, we identify the need of effective and efficient methods to conduct tweet sentiment analysis. This paper aims to achieve a high level of performance for classifying tweets with sentiment information. We propose a feasible solution which improves the level of accuracy with good time efficiency. Specifically, we develop a novel feature combination scheme which utilizes the sentiment lexicons and the extracted tweet unigrams of high information gain. We evaluate the performance of six popular machine learning classifiers among which the Naive Bayes Multinomial (NBM) classifier achieves the accuracy rate of 84.60% and takes a few minutes to complete classifying thousands of tweets.
{"title":"Enhanced Twitter Sentiment Analysis by Using Feature Selection and Combination","authors":"Ang Yang, Jun Zhang, Lei Pan, Yang Xiang","doi":"10.1109/SocialSec2015.9","DOIUrl":"https://doi.org/10.1109/SocialSec2015.9","url":null,"abstract":"Tweet sentiment analysis is an important research topic. An accurate and timely analysis report could give good indications on the general public's opinions. After reviewing the current research, we identify the need of effective and efficient methods to conduct tweet sentiment analysis. This paper aims to achieve a high level of performance for classifying tweets with sentiment information. We propose a feasible solution which improves the level of accuracy with good time efficiency. Specifically, we develop a novel feature combination scheme which utilizes the sentiment lexicons and the extracted tweet unigrams of high information gain. We evaluate the performance of six popular machine learning classifiers among which the Naive Bayes Multinomial (NBM) classifier achieves the accuracy rate of 84.60% and takes a few minutes to complete classifying thousands of tweets.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122622787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-11-16DOI: 10.1109/SocialSec2015.11
Peixin Chen, Xiaofeng Wang, Jinshu Su
The Hierarchical Identity-Based Encryption (HIBE) scheme can efficiently provide confidential communication and privacy protection to online social networks. However, the inherent key escrow problem and the secure key distributing problem primarily hinder the widespread adoption of the cryptographic scheme in practice. To address the key escrow problem, this paper introduces a provably secure escrow-free model, which employs multiple Key Privacy Authorities (KPAs) to restrict the power of Public Key Generators (PKGs) in HIBE scheme. To achieve the goal of secure key distributing, this paper proposes an efficient mechanism which imposes user calculated blinding factors when distributing private keys. We instantiate the proposed model into an trustworthy and secure HIBE scheme called T-HIBE scheme, and prove that the scheme is IND-ID-CCA secure under standard model.
{"title":"T-HIBE: A Trustworthy HIBE Scheme for the OSN Privacy Protection","authors":"Peixin Chen, Xiaofeng Wang, Jinshu Su","doi":"10.1109/SocialSec2015.11","DOIUrl":"https://doi.org/10.1109/SocialSec2015.11","url":null,"abstract":"The Hierarchical Identity-Based Encryption (HIBE) scheme can efficiently provide confidential communication and privacy protection to online social networks. However, the inherent key escrow problem and the secure key distributing problem primarily hinder the widespread adoption of the cryptographic scheme in practice. To address the key escrow problem, this paper introduces a provably secure escrow-free model, which employs multiple Key Privacy Authorities (KPAs) to restrict the power of Public Key Generators (PKGs) in HIBE scheme. To achieve the goal of secure key distributing, this paper proposes an efficient mechanism which imposes user calculated blinding factors when distributing private keys. We instantiate the proposed model into an trustworthy and secure HIBE scheme called T-HIBE scheme, and prove that the scheme is IND-ID-CCA secure under standard model.","PeriodicalId":121098,"journal":{"name":"2015 International Symposium on Security and Privacy in Social Networks and Big Data (SocialSec)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129889101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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