Authors:Majid Nateghizad;Zekeriya Erkin andReginald L. Lagendijk
Affiliation:Cyber Security Group, Department of Intelligent Systems, Delft University of Technology and The Netherlands
Keyword(s):Searching in Encrypted Databases, Homomorphic Encryption, Statistical Query, Indexing, Privacy.
RelatedOntology Subjects/Areas/Topics:Applied Cryptography ;Cryptographic Techniques and Key Management ;Data and Application Security and Privacy ;Data Engineering ;Database Security and Privacy ;Databases and Data Security ;Information and Systems Security ;Privacy ;Security and Privacy for Big Data ;Security and Privacy in IT Outsourcing ;Security in Information Systems
Abstract:It is astonishing to see more and more services built on user-oriented data, providing numerous tools to improve ones daily life. Nowadays, data collected from numerous sources is being used to monitor daily activities, i.e., monitoring patients. These innovations allow for more cost-efficient and scalable solutions. Nevertheless, these types of services can pose a threat to the privacy of individuals due to the possibility of leaking highly privacy-sensitive data. Therefore, it is essential to design such systems in a privacy-preserving manner. Inspired by a real-life project in the health-care domain, we propose to secure the data using encryption, while enabling the involved parties to run queries directly on this encrypted data. A vital component of such a system is searching for specific data entries within a large dataset. In this work, we present two cryptographic protocols that complete such a query by creating an encrypted vector in a simulation secure way. These vectors consist of a 1 for intended database entry, whereas other items would be represented as a 0. By creating index tables before the execution of the queries, it has become possible to execute a search query with high performance. As we show in our analyses, it takes less than one second to find the matching encrypted data-entry within a database with 100K records. Our proposal is generic, can be applied to several application domains, and practically compared to similar works.(More)
It is astonishing to see more and more services built on user-oriented data, providing numerous tools to improve ones daily life. Nowadays, data collected from numerous sources is being used to monitor daily activities, i.e., monitoring patients. These innovations allow for more cost-efficient and scalable solutions. Nevertheless, these types of services can pose a threat to the privacy of individuals due to the possibility of leaking highly privacy-sensitive data. Therefore, it is essential to design such systems in a privacy-preserving manner. Inspired by a real-life project in the health-care domain, we propose to secure the data using encryption, while enabling the involved parties to run queries directly on this encrypted data. A vital component of such a system is searching for specific data entries within a large dataset. In this work, we present two cryptographic protocols that complete such a query by creating an encrypted vector in a simulation secure way. These vectors consist of a 1 for intended database entry, whereas other items would be represented as a 0. By creating index tables before the execution of the queries, it has become possible to execute a search query with high performance. As we show in our analyses, it takes less than one second to find the matching encrypted data-entry within a database with 100K records. Our proposal is generic, can be applied to several application domains, and practically compared to similar works.