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Andreas Peter
Researcher at University of Twente
Publications - 72
Citations - 1383
Andreas Peter is an academic researcher from University of Twente. The author has contributed to research in topics: Encryption & Computer science. The author has an hindex of 14, co-authored 62 publications receiving 1061 citations. Previous affiliations of Andreas Peter include Technische Universität Darmstadt & Information Technology University.
Papers
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Journal ArticleDOI
A Survey of Provably Secure Searchable Encryption
TL;DR: The notion of provably secure searchable encryption (SE) is surveyed by giving a complete and comprehensive overview of the two main SE techniques: searchable symmetric encryption (SSE) and public key encryption with keyword search (PEKS).
Journal ArticleDOI
Efficiently Outsourcing Multiparty Computation Under Multiple Keys
TL;DR: This work proposes a novel technique based on additively homomorphic encryption that is efficient, requires no user interaction whatsoever (except for data upload and download), and allows evaluating any dynamically chosen function on inputs encrypted under different public keys.
Book ChapterDOI
Redactable signatures for tree-structured data: definitions and constructions
Christina Brzuska,Heike Busch,Oezguer Dagdelen,Marc Fischlin,Martin Franz,Stefan Katzenbeisser,Mark Manulis,Cristina Onete,Andreas Peter,Bertram Poettering,Dominique Schröder +10 more
TL;DR: This work revisits Kundu and Bertino's work and gives rigorous security models for the redactable signatures for tree-structured data, relate the notions, and give a construction that can be proven secure under standard cryptographic assumptions.
Posted Content
Efficiently Outsourcing Multiparty Computation under Multiple Keys.
TL;DR: In this article, the authors proposed additively homomorphic encryption (AHE) for secure multiparty computation, which allows evaluating any dynamically chosen function on inputs encrypted under different public keys.
Proceedings ArticleDOI
FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic
Thijs van Ede,Riccardo Bortolameotti,Andrea Continella,Jingjing Ren,Daniel J. Dubois,Martina Lindorfer,David Choffnes,Maarten van Steen,Andreas Peter +8 more
TL;DR: FlowPrint is proposed, a semi-supervised approach for fingerprinting mobile apps from (encrypted) network traffic that automatically finds temporal correlations among destination-related features of network traffic and uses these correlations to generate app fingerprints.