The Experts below are selected from a list of 228972 Experts worldwide ranked by ideXlab platform
Tran Khanh Dang - One of the best experts on this subject based on the ideXlab platform.
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semantic aware obfuscation for location privacy at Database Level
International Conference on Information and Communication Technology, 2013Co-Authors: Tran Khanh DangAbstract:Although many techniques have been proposed to deal with location privacy problem, which is one of popular research issues in location based services, some limitations still remain and hence they cannot be applied to the real world. One of the most typical proposed techniques is obfuscation that preserves location privacy by degrading the quality of user's location information. But the less exact information, the more secure and the less effective services can be supported. Thus the goal of obfuscated techniques is balancing between privacy and quality of services. However, most of obfuscated techniques are separated from Database Level, leading to other security and performance issues. In this paper, we introduce a new approach to protect location privacy at Database Level, called Semantic Bob-tree, an index structure that is based on Bdual-tree and Bob-tree and contains semantic aware information in its nodes. It can achieve high Level of privacy and keep up the quality of services.
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ICT-EurAsia - Semantic-Aware obfuscation for location privacy at Database Level
Lecture Notes in Computer Science, 2013Co-Authors: Tran Khanh DangAbstract:Although many techniques have been proposed to deal with location privacy problem, which is one of popular research issues in location based services, some limitations still remain and hence they cannot be applied to the real world. One of the most typical proposed techniques is obfuscation that preserves location privacy by degrading the quality of user's location information. But the less exact information, the more secure and the less effective services can be supported. Thus the goal of obfuscated techniques is balancing between privacy and quality of services. However, most of obfuscated techniques are separated from Database Level, leading to other security and performance issues. In this paper, we introduce a new approach to protect location privacy at Database Level, called Semantic Bob-tree, an index structure that is based on Bdual-tree and Bob-tree and contains semantic aware information in its nodes. It can achieve high Level of privacy and keep up the quality of services.
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A Hilbert-based framework for preserving privacy in location-based services
International Journal of Intelligent Information and Database Systems, 2013Co-Authors: Tran Khanh Dang, Josef KüngAbstract:Preserving user's privacy has recently drawn special attention in the field of location-based services and many techniques such as k-anonymity or obfuscation have been suggested to protect user's privacy. All of these traditional techniques are, however, geometry-based and separated from the Database Level. This separation causes the query processing to involve in two phases, querying the Database to retrieve the exact locations of users and then modifying them to decrease the quality of this information. This two-phase process is time-consuming due to the number of disk accesses required to retrieve the user's exact location. Also, these geometry-based techniques cannot guarantee location privacy when the adversary gains knowledge about the geography of the obfuscated region. We address these problems by proposing Hilbert-based framework for preserving user's privacy and B
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semantic b ob tree a new obfuscation technique for location privacy protection
Advances in Mobile Multimedia, 2012Co-Authors: Thu Le Thi Bao, Tran Khanh DangAbstract:The problem of preserving user's privacy in Location Based Services (LBS) has been researched increasingly. One of the techniques is obfuscation which preserves location privacy by degrading the quality of user's location information. But the less exact information, the more secure and the less effective services and most of the techniques are separated from Database Level. In this paper, we introduce a new approach to protect location privacy at Database Level, called Semantic Bob-tree, an index structure contains semantic aware information in its nodes. It can achieve high Level of privacy and keep up the quality of services.
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MoMM - Semantic B ob -tree: a new obfuscation technique for location privacy protection
Proceedings of the 10th International Conference on Advances in Mobile Computing & Multimedia - MoMM '12, 2012Co-Authors: Thu Le Thi Bao, Tran Khanh DangAbstract:The problem of preserving user's privacy in Location Based Services (LBS) has been researched increasingly. One of the techniques is obfuscation which preserves location privacy by degrading the quality of user's location information. But the less exact information, the more secure and the less effective services and most of the techniques are separated from Database Level. In this paper, we introduce a new approach to protect location privacy at Database Level, called Semantic Bob-tree, an index structure contains semantic aware information in its nodes. It can achieve high Level of privacy and keep up the quality of services.
M. Indra Devi - One of the best experts on this subject based on the ideXlab platform.
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Fragmented query parse tree based SQL injection detection system for web applications
2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16), 2016Co-Authors: B. Deva Priyaa, M. Indra DeviAbstract:Increasing use of Database driven web applications every day causes attacks on those web applications are also increasing. The common web application attack is SQL Injection attack or code injection or insertion of SQL query via input data from the client to the application. There are many detection techniques focused on the SQL structure at the application Level are available. Those techniques failed to detect some of the attacks at the Database Level. Many existing approaches were proposed to detect the attack at the Database Level. The existing approach uses SVM classification for classification, which is the supervised learning algorithm, uses the syntactic and semantic features of the query parse tree. It takes more time for preprocessing of the query parse tree. In this paper, we fragmented the query parse tree to increase the speed of the preprocessing. The internal query tree can be obtained from the Database log. To get instances for classification, the query tree is converted to n — dimensional feature vector by using multi — dimensional sequence. The semantic features are used as the component of feature vectors. And also the syntactic and semantic features are used to generate multi — dimensional sequences. Then the extracted feature is converted into a numeric value, if the feature contains any string value. Experimental results show that the proposed approach is more accurate and fast in detecting the attacks than existing approaches.
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Hybrid SQL injection detection system
2016 3rd International Conference on Advanced Computing and Communication Systems (ICACCS), 2016Co-Authors: B. Deva Priyaa, M. Indra DeviAbstract:The use of Database driven web applications are increasing every day. Attacks on those web applications are also increasing. One of the common web application attacks is SQL Injection attack. These attacks are a code injection or insertion of SQL query via input data from the client to the application. There are many detection techniques implemented, but they have focused on the SQL structure at the application Level. So those techniques failed to detect some of the attacks at the Database Level. The existing approaches use classification techniques and suitable kernel functions to detect the attack at the Database Level. As the SVM classification is the supervised learning algorithm, the unknown attacks can't be detected. In this paper, we propose a hybrid framework using the EDADT (Efficient Data Adaptive Decision Tree) algorithm which is the semi - supervised algorithm and SVM classification algorithm. It uses the internal query tree from the Database log for good performance of framework. To get internal query tree, the query tree is converted to n - dimensional feature vector by using multi - dimensional sequence. The semantic features are used as the component of feature vector. And also the syntactic and semantic feature is used to generate multi - dimensional sequences. Then the extracted feature is converted into numeric value, if the feature contains any string value. Experimental results show that the proposed approach is more accurate in detecting the attacks than existing approaches.
Josef Küng - One of the best experts on this subject based on the ideXlab platform.
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A Hilbert-based framework for preserving privacy in location-based services
International Journal of Intelligent Information and Database Systems, 2013Co-Authors: Tran Khanh Dang, Josef KüngAbstract:Preserving user's privacy has recently drawn special attention in the field of location-based services and many techniques such as k-anonymity or obfuscation have been suggested to protect user's privacy. All of these traditional techniques are, however, geometry-based and separated from the Database Level. This separation causes the query processing to involve in two phases, querying the Database to retrieve the exact locations of users and then modifying them to decrease the quality of this information. This two-phase process is time-consuming due to the number of disk accesses required to retrieve the user's exact location. Also, these geometry-based techniques cannot guarantee location privacy when the adversary gains knowledge about the geography of the obfuscated region. We address these problems by proposing Hilbert-based framework for preserving user's privacy and B
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NTMS - OST-Tree: An Access Method for Obfuscating Spatio-Temporal Data in Location Based Services
2011 4th IFIP International Conference on New Technologies Mobility and Security, 2011Co-Authors: Tran Khanh Dang, Josef KüngAbstract:Since the development of location-based services, privacy-preserving has gained special attention and many algorithms aiming at protecting user's privacy have been created such as obfuscation or k-anonymity. However, all of these researches separate the algorithms from the Database Level. Thus, the querying process has two phases, querying the Database to retrieve the accurate positions of users and then modifying them to decrease the quality of location information. This two-phase process is time-consuming due to the number of disk accesses required to retrieve the user's exact position. We address this problem by proposing OST-tree, a structure that embeds the user's privacy policy in its node and obfuscates the spatio-temporal data. Experiments show that OST-tree provides an improvement over the algorithm separated from the Database Level for both querying costs and user's privacy protection.
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ACIIDS (1) - B ob -tree: an efficient B + -tree based index structure for geographic-aware obfuscation
Intelligent Information and Database Systems, 2011Co-Authors: Tran Khanh Dang, Josef KüngAbstract:The privacy protection of personal location information increasingly gains special attention in the field of location-based services, and obfuscation is the most popular technique aiming at protecting this sensitive information. However, all of the conventional obfuscation techniques are geometry-based and separated from the Database Level. Thus, the query processing has two timeconsuming phases due to the number of disk accesses required to retrieve the user's exact location, and the location obfuscation. Also, since these techniques are geometry-based, they cannot assure location privacy when the adversary has knowledge about the geography of the obfuscated region. We address these problems by proposing Bob-tree, an index structure that is based on Bdual-tree and contains geographic-aware information on its nodes. Experiments show that Bob-tree provides a significant improvement over the algorithm separated from the Database Level for query processing time and location privacy protection.
Patrick Valduriez - One of the best experts on this subject based on the ideXlab platform.
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Refresco: Improving Query Performance Through Freshness Control in a Database Cluster
2004Co-Authors: Cécile Le Pape, Stéphane Gançarski, Patrick ValduriezAbstract:We consider the use of a cluster system for managing autonomous Databases. In order to improve the performance of read-only queries, we strive to exploit user requirements on replica freshness. Assuming mono-master lazy replication, we propose a freshness model to help specifying the required freshness Level for queries. We propose an algorithm to optimize the routing of queries on slave nodes based on the freshness requirements. Our approach uses non intrusive techniques that preserve application and Database autonomy. We provide an experimental validation based on our prototype Refresco. The results show that freshness control can help increase query throughput significantly. They also show significant improvement when freshness requirements are specified at the relation Level rather than at the Database Level.
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CoopIS/DOA/ODBASE (1) - Refresco: Improving Query Performance Through Freshness Control in a Database Cluster
On the Move to Meaningful Internet Systems 2004: CoopIS DOA and ODBASE, 2004Co-Authors: Cécile Le Pape, Stéphane Gançarski, Patrick ValduriezAbstract:We consider the use of a cluster system for managing autonomous Databases. In order to improve the performance of read-only queries, we strive to exploit user requirements on replica freshness. Assuming mono-master lazy replication, we propose a freshness model to help specifying the required freshness Level for queries. We propose an algorithm to optimize the routing of queries on slave nodes based on the freshness requirements. Our approach uses non intrusive techniques that preserve application and Database autonomy. We provide an experimental validation based on our prototype Refresco. The results show that freshness control can help increase query throughput significantly. They also show significant improvement when freshness requirements are specified at the relation Level rather than at the Database Level.
B. Deva Priyaa - One of the best experts on this subject based on the ideXlab platform.
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Fragmented query parse tree based SQL injection detection system for web applications
2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16), 2016Co-Authors: B. Deva Priyaa, M. Indra DeviAbstract:Increasing use of Database driven web applications every day causes attacks on those web applications are also increasing. The common web application attack is SQL Injection attack or code injection or insertion of SQL query via input data from the client to the application. There are many detection techniques focused on the SQL structure at the application Level are available. Those techniques failed to detect some of the attacks at the Database Level. Many existing approaches were proposed to detect the attack at the Database Level. The existing approach uses SVM classification for classification, which is the supervised learning algorithm, uses the syntactic and semantic features of the query parse tree. It takes more time for preprocessing of the query parse tree. In this paper, we fragmented the query parse tree to increase the speed of the preprocessing. The internal query tree can be obtained from the Database log. To get instances for classification, the query tree is converted to n — dimensional feature vector by using multi — dimensional sequence. The semantic features are used as the component of feature vectors. And also the syntactic and semantic features are used to generate multi — dimensional sequences. Then the extracted feature is converted into a numeric value, if the feature contains any string value. Experimental results show that the proposed approach is more accurate and fast in detecting the attacks than existing approaches.
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Hybrid SQL injection detection system
2016 3rd International Conference on Advanced Computing and Communication Systems (ICACCS), 2016Co-Authors: B. Deva Priyaa, M. Indra DeviAbstract:The use of Database driven web applications are increasing every day. Attacks on those web applications are also increasing. One of the common web application attacks is SQL Injection attack. These attacks are a code injection or insertion of SQL query via input data from the client to the application. There are many detection techniques implemented, but they have focused on the SQL structure at the application Level. So those techniques failed to detect some of the attacks at the Database Level. The existing approaches use classification techniques and suitable kernel functions to detect the attack at the Database Level. As the SVM classification is the supervised learning algorithm, the unknown attacks can't be detected. In this paper, we propose a hybrid framework using the EDADT (Efficient Data Adaptive Decision Tree) algorithm which is the semi - supervised algorithm and SVM classification algorithm. It uses the internal query tree from the Database log for good performance of framework. To get internal query tree, the query tree is converted to n - dimensional feature vector by using multi - dimensional sequence. The semantic features are used as the component of feature vector. And also the syntactic and semantic feature is used to generate multi - dimensional sequences. Then the extracted feature is converted into numeric value, if the feature contains any string value. Experimental results show that the proposed approach is more accurate in detecting the attacks than existing approaches.
