Show simple item record

dc.contributor.authorCarter, Henry
dc.contributor.authorAmrutkar, Chaitrali
dc.contributor.authorDacosta, Italo
dc.contributor.authorTraynor, Patrick
dc.date.accessioned2012-02-07T16:32:28Z
dc.date.available2012-02-07T16:32:28Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/1853/42367
dc.descriptionResearch area: Information Security and Cryptography, Networking and Communications
dc.descriptionResearch topic: Privacy-Preserving Computation, Mobile Application Security
dc.description.abstractThe growth of smartphone capability has led to an explosion of new applications. Many of the most useful apps use context-sensitive data, such as GPS location or social network information. In these cases, users may not be willing to release personal information to untrusted parties. Currently, the solutions to performing computation on encrypted inputs use garbled circuits combined with a variety of optimizations. However, the capability of resource-constrained smartphones for evaluating garbled circuits in any variation is uncertain in practice. In [1], it is shown that certain garbled circuit evaluations can be optimized by using homomorphic encryption. In this paper, we take this concept to its logical extreme with Efficient Mobile Oblivious Computation (EMOC), a technique that completely replaces garbled circuits with homomorphic operations on ciphertexts. We develop applications to securely solve the millionaire’s problem, send tweets based on location, and compute common friends in a social network, then prove equivalent privacy guarantees to analogous constructions using garbled circuits. We then demonstrate up to 68% runtime reduction from the most efficient garbled circuit implementation. In so doing, we demonstrate a practical technique for developing privacy-preserving applications on the mobile platform.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesSCS Technical Report ; GT-CS-11-11en_US
dc.subjectEfficient Mobile Oblivious Computation (EMOC)en_US
dc.subjectEncrypted dataen_US
dc.subjectGarbled circuiten_US
dc.subjectHash functionen_US
dc.subjectHomomorphic cryptographyen_US
dc.subjectMobile devicesen_US
dc.subjectPrivacy-preservingen_US
dc.subjectSecurityen_US
dc.subjectSocial networksen_US
dc.titleEfficient Oblivious Computation Techniques for Privacy-Preserving Mobile Applicationsen_US
dc.typeTechnical Reporten_US
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computing
dc.contributor.corporatenameGeorgia Institute of Technology. School of Computer Science


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record