dc.contributor.author | Gjerdrum, Anders Tungeland | |
dc.contributor.author | Pettersen, Robert | |
dc.contributor.author | Johansen, Håvard D. | |
dc.contributor.author | Johansen, Dag | |
dc.date.accessioned | 2019-02-11T08:24:05Z | |
dc.date.available | 2019-02-11T08:24:05Z | |
dc.date.issued | 2018-07-14 | |
dc.description.abstract | Cloud providers offering Software-as-a-Service (SaaS) are increasingly being trusted by customers to store sensitive data. Companies often monetize such personal data through curation and analysis, providing customers with personalized application experiences and targeted advertisements. Personal data is often accompanied by strict privacy and security policies, requiring data processing to be governed by non-trivial enforcement mechanisms. Moreover, to offset the cost of hosting the potentially large amounts of data privately, SaaS companies even employ Infrastructure-as-a-Service (IaaS) cloud providers not under the direct supervision of the administrative entity responsible for the data. Intel Software Guard Extensions (SGX) is a recent trusted computing technology that can mitigate some of these privacy and security concerns through the remote attestation of computations, establishing trust on hardware residing outside the administrative domain. This paper investigates and demonstrates the added cost of using SGX, and further argues that great care must be taken when designing system software in order to avoid the performance penalty incurred by trusted computing. We describe these costs and present eight specific principles that application authors should follow to increase the performance of their trusted computing systems. | en_US |
dc.description | Accepted manuscript version of the following article Gjerdrum, A.T., Pettersen, R., Johansen, H.D. & Johansen, D. (2018). Performance principles for trusted computing with intel SGX. <i>Communications in Computer and Information Science, 864</i>. © Springer International Publishing AG, part of Springer Nature 2018. Published version available at <a href=https://doi.org/10.1007/978-3-319-94959-8_1> https://doi.org/10.1007/978-3-319-94959-8_1</a>. | en_US |
dc.identifier.citation | Gjerdrum, A.T., Pettersen, R., Johansen, H.D. & Johansen, D. (2018). Performance principles for trusted computing with intel SGX. <i>Communications in Computer and Information Science, 864</i>. https://doi.org/10.1007/978-3-319-94959-8_1 | en_US |
dc.identifier.cristinID | FRIDAID 1628273 | |
dc.identifier.doi | 10.1007/978-3-319-94959-8_1 | |
dc.identifier.issn | 1865-0929 | |
dc.identifier.issn | 1865-0937 | |
dc.identifier.uri | https://hdl.handle.net/10037/14666 | |
dc.language.iso | eng | en_US |
dc.publisher | Springer Verlag (Germany) | en_US |
dc.relation.ispartof | Gjerdrum, A.T. (2020). Diggi: A Distributed Serverless Runtime for Developing Trusted Cloud Services. (Doctoral thesis). <a href=https://hdl.handle.net/10037/19607>https://hdl.handle.net/10037/19607</a>. | |
dc.relation.journal | Communications in Computer and Information Science | |
dc.relation.projectID | info:eu-repo/grantAgreement/RCN/IKTPLUSS/263248/Norway/Protecting Shared Data with Privacy Automatons// | en_US |
dc.relation.projectID | info:eu-repo/grantAgreement/RCN/INTPART/250138/Norway/Trans-Atlantic Corpore Sano// | en_US |
dc.rights.accessRights | openAccess | en_US |
dc.subject | VDP::Mathematics and natural science: 400::Information and communication science: 420 | en_US |
dc.subject | VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420 | en_US |
dc.subject | Privacy | en_US |
dc.subject | Security | en_US |
dc.subject | Cloud computing | en_US |
dc.subject | Trusted computing | en_US |
dc.subject | Performance | en_US |
dc.title | Performance principles for trusted computing with intel SGX | en_US |
dc.type | Journal article | en_US |
dc.type | Tidsskriftartikkel | en_US |
dc.type | Peer reviewed | en_US |