Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Martin Pettai"'
Autor:
Marlon Dumas, Reedik Tuuling, Joosep Jääger, Maksym Yerokhin, Aivo Toots, Raimundas Matulevičius, Martin Pettai, Alisa Pankova, Pille Pullonen-Raudvere, Luciano García-Bañuelos, Peeter Laud
Publikováno v:
International Journal on Software Tools for Technology Transfer. 24:183-203
Privacy regulations, such as GDPR, impose strict requirements to organizations that store and process private data. Privacy-enhancing technologies (PETs), such as secure multi-party computation and differential privacy, provide mechanisms to perform
Publikováno v:
Proceedings on Privacy Enhancing Technologies, Vol 2020, Iss 2, Pp 175-208 (2020)
The meaning of differential privacy (DP) is tightly bound with the notion of distance on databases, typically defined as the number of changed rows. Considering the semantics of data, this metric may be not the most suitable one, particularly when a
Autor:
Maksym Yerokhin, Peeter Laud, Raimundas Matulevičius, Luciano García-Bañuelos, Marlon Dumas, Alisa Pankova, Pille Pullonen, Jake Tom, Reedik Tuuling, Aivo Toots, Martin Pettai
Publikováno v:
Fundamental Approaches to Software Engineering ISBN: 9783030167219
FASE
FASE
Pleak is a tool to capture and analyze privacy-enhanced business process models to characterize and quantify to what extent the outputs of a process leak information about its inputs. Pleak incorporates an extensible set of analysis plugins, which en
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a36a2212210014c810ff5d5991a2722c
https://doi.org/10.1007/978-3-030-16722-6_18
https://doi.org/10.1007/978-3-030-16722-6_18
Publikováno v:
PLAS@CCS
The sensitivity of a function is the maximum change of its output for a unit change of its input. In this paper we present a method for determining the sensitivity of SQL queries, seen as functions from databases to datasets, where the change is meas
Autor:
Reedik Tuuling, Jake Tom, Aivo Toots, Raimundas Matulevičius, Peeter Laud, Alisa Pankova, Martin Pettai, Luciano García-Bañuelos, Pille Pullonen, Maksym Yerokhin, Marlon Dumas
Publikováno v:
Informatik Spektrum. 42:354-355
Autor:
Martin Pettai, Peeter Laud
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783662544549
POST
POST
Workflows are a notation for business processes, focusing on tasks and data flows between them. We have designed and implemented a method for analyzing leakages in workflows by combining differential privacy and mutual information. The input of the m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6896532c30f2f282bd880d11a38fd4bb
https://doi.org/10.1007/978-3-662-54455-6_14
https://doi.org/10.1007/978-3-662-54455-6_14
Autor:
Peeter Laud, Martin Pettai
Publikováno v:
ACSAC
We consider how to perform privacy-preserving analyses on private data from different data providers and containing personal information of many different individuals. We combine differential privacy and secret sharing based secure multiparty computa
Autor:
Peeter Laud, Martin Pettai
Publikováno v:
CSF
We describe an automatic analysis to check secure multi-party computation protocols against privacy leaks. The analysis is sound -- a protocol that is deemed private does not leak anything about its private inputs, even if active attacks are performe
Publikováno v:
PETShop@CCS
In this paper, we discuss the design choices and initial experiences with a domain-specific language and its optimizing compiler for specifying protocols for secure computation. We give the rationale of the design, describe the translation steps, the
Autor:
Peeter Laud, Martin Pettai
Publikováno v:
SOFSEM 2012: Theory and Practice of Computer Science ISBN: 9783642276590
SOFSEM
SOFSEM
We present an information-flow type system for a distributed object-oriented language with active objects, asynchronous method calls and futures. The variables of the program are classified as high and low. We allow while cycles with high guards to b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7731f5f40ce9e3a07091abd4b793d7d1
https://doi.org/10.1007/978-3-642-27660-6_47
https://doi.org/10.1007/978-3-642-27660-6_47