Journal: Lecture Notes in Computer Science

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Abbreviation

LNCS

Publisher

Springer

Journal Volumes

ISSN

0302-9743
1611-3349

Description

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Publications 1 - 10 of 2647
  • Pretschner, Alexander; Massacci, Fabio; Hilty, Manuel (2007)
    Lecture Notes in Computer Science ~ Trust, privacy and security in digital business
  • Clemente, Jhoirene; Hromkovič, Juraj; Komm, Dennis; et al. (2016)
    Lecture Notes in Computer Science ~ Combinatorial Algorithms
  • Chen, Xiaoran; Tanner, Christine; Goksel, Orcun; et al. (2016)
    Lecture Notes in Computer Science ~ Medical Imaging and Augmented Reality: 7th International Conference, MIAR 2016, Bern, Switzerland, August 24-26, 2016, Proceedings
  • Bertola, Numa J.; Smith, Ian F.C. (2018)
    Lecture Notes in Computer Science ~ Advanced Computing Strategies for Engineering
  • Hofheinz, Dennis; Hostáková, Kristina; Kastner, Julia Dorothea Beate; et al. (2024)
    Lecture Notes in Computer Science ~ Public-Key Cryptography – PKC 2024
    Selective opening (SO) security is a security notion for public-key encryption schemes that captures security against adaptive corruptions of senders. SO security comes in chosen-plaintext (SO-CPA) and chosen-ciphertext (SO-CCA) variants, neither of which is implied by standard security notions like IND-CPA or IND-CCA security.
  • Christakis, Maria; Müller, Peter; Wüstholz, Valentin (2012)
    Lecture Notes in Computer Science ~ FM 2012: Formal Methods : 18th International Symposium, Paris, France, August 27-31, 2012 : proceedings
  • Käser, Tanja; Klingler, Severin; Schwing, Alexander G.; et al. (2014)
    Lecture Notes in Computer Science ~ Intelligent Tutoring Systems
    Modeling and predicting student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for student modeling is Bayesian Knowledge Tracing (BKT). BKT models, however, lack the ability to describe the hierarchy and relationships between the different skills of a learning domain. In this work, we therefore aim at increasing the representational power of the student model by employing dynamic Bayesian networks that are able to represent such skill topologies. To ensure model interpretability, we constrain the parameter space. We evaluate the performance of our models on five large-scale data sets of different learning domains such as mathematics, spelling learning and physics, and demonstrate that our approach outperforms BKT in prediction accuracy on unseen data across all learning domains.
  • New Preimage Attacks Against Reduced SHA-1
    Item type: Conference Paper
    Knellwolf, Simon; Khovratovich, Dmitry (2012)
    Lecture Notes in Computer Science ~ Advances in cryptology : proceedings
  • Pappas, Christos; Reischuk, Raphael M.; Perrig, Adrian (2016)
    Lecture Notes in Computer Science ~ Open Problems in Network Security. IFIP WG 11.4 International Workshop, iNetSec 2015, Zurich, Switzerland, October 29, 2015, Revised Selected Papers
  • Böckenhauer, Hans-Joachim; Di Caro, Lucia; Unger, Walter (2018)
    Lecture Notes in Computer Science ~ Adventures Between Lower Bounds and Higher Altitudes
Publications 1 - 10 of 2647